{"as_of":"2026-08-17T00:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0fa7bbd60d0320a794cc8bb81f2f6ecee8576c7d0b3354315c2b93b4ec3eef14","coverage":[{"denominator":73,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":73,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T14:43:06.126218Z","state":"measured"},{"denominator":73,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":73,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1908.02738/citation-record","integrity":"/paper/1908.02738/integrity","json":"/paper/1908.02738/citation-record.json","paper":"/paper/1908.02738"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.301125Z","title":"Cross-words reference template for dtw-based speech recognition systems","venue":null,"work_id":"0f50b803-412a-463e-8e00-6894d2bba962","year":2003},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.808335Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:0b924fd88451d6feb9353d939024deb6bed56fef4a25130ba1224329b945e4c7","observation_id":"16912ace-f83c-46f9-a057-f5d9a6cd74b0","resolution":{"observed_at":"2026-08-14T14:43:07.310414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.280720Z","title":"Unsupervised convolutional neural networks for motion estimation","venue":null,"work_id":"fbcac98b-8caa-43f8-9f89-826f04c7011a","year":2016},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.813461Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:767d1619ebdc6e68aec52c5e3f92352c854515da30e871eddd820f685de63d4c","observation_id":"eab8d2f8-8fdd-45e1-8b40-8cb5fde38330","resolution":{"observed_at":"2026-08-14T14:43:07.289223Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.259456Z","title":"Towards a coherent statistical framework for dense deformable template estimation","venue":null,"work_id":"7e4624d8-2c5f-451c-8a49-9829150e7b27","year":2007},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.818948Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:54d62980c0cba04170393aa9498830b91fdb3e763841502133de587df9b69ae3","observation_id":"63854986-9fb8-4bd9-9ad5-9f0c74f77781","resolution":{"observed_at":"2026-08-14T14:43:07.265612Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1701.07875","last_updated":"2017-12-06T20:01:54Z","snapshot_observed_at":"2026-08-14T21:19:18.245847Z","submitted_at":"2017-01-26T21:10:29Z","title":"Wasserstein GAN","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1701.07875","snapshot_observed_at":"2026-08-14T14:43:05.824467Z","title":"Wasserstein gan","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.824467Z"},"links":{"cited_paper":"/paper/1701.07875","citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:e066a5e77ba92581a7d96772da79bd027d45dfdb85306d01ec823bdea409d485","observation_id":"a10dbf90-8c97-4207-9e22-6f1781092753","resolution":{"observed_at":"2026-08-14T14:43:05.824467Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.242230Z","title":"Ashburner","venue":null,"work_id":"4a5c47a9-1009-494a-a4ee-b6e1ba64bed4","year":2007},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.830045Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:f6d801a2901f1fb739cb5e5d66e04359bee312b414eca36177e5f0e0020b7a7a","observation_id":"bf780c60-653f-4f95-9cc6-050781aceced","resolution":{"observed_at":"2026-08-14T14:43:07.248102Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:05.834840Z","title":"Symmetric diffeo- morphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.834840Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:81595b621c527515edb1915ab128748b97ffec4509c7bbdf3d0222107b437ad2","observation_id":"dcaf717c-287e-43da-8d7e-0de5dc12f9f9","resolution":{"observed_at":"2026-08-14T14:43:05.834840Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.210934Z","title":"Bajcsy and S","venue":null,"work_id":"9265ee08-43cd-4b1b-a5da-d306d5690c9e","year":1989},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.838878Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:1f35b58e785ac223b3711608348865e87965e27a9580d0e2ea870286d489a920","observation_id":"c6d8a8d3-94c1-491e-af53-651f6683ae5f","resolution":{"observed_at":"2026-08-14T14:43:07.217346Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.195743Z","title":"Balakrishnan, A","venue":null,"work_id":"2dc599d5-067f-4039-b52d-ccc2578a609d","year":2018},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.842604Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:05df99f64035993c9e37d5fb3a13417c188b3c9acc5927b4a21009117a9c6aa3","observation_id":"4fda5512-af33-4ef4-bb49-cf9bfc70a347","resolution":{"observed_at":"2026-08-14T14:43:07.200731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.180497Z","title":"Balakrishnan, A","venue":null,"work_id":"51c09068-f7cf-44d0-b1f9-4ccb4b23d161","year":2018},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.846465Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:4537db06c0d3e336a42b8db985faae7377fb866fe569e53f0c158781d9c2a192","observation_id":"1d034b1d-1937-4e2f-9ad5-c3532e3ca870","resolution":{"observed_at":"2026-08-14T14:43:07.185203Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.155549Z","title":"Beg et al","venue":null,"work_id":"3b3cb157-2232-4c08-a94a-334c00ddda07","year":2005},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.850382Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:adafe594813c0637b0ec883b32d948a5c932c2d0d4aec50d23b552d4cbdd396f","observation_id":"1ffe62c2-c3ef-4a88-b098-e58e4c591d94","resolution":{"observed_at":"2026-08-14T14:43:07.160383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.137752Z","title":"High accuracy optical flow estimation based on a theory for warping","venue":null,"work_id":"0459b156-4e08-4650-a6dc-ccf389ef290f","year":2004},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.854288Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:4babc78d3995e8244e638fdf752b6412fbd08392845de2abe634bffa127cdb61","observation_id":"38bf0587-dc56-4510-ba2e-79e58cd677de","resolution":{"observed_at":"2026-08-14T14:43:07.144508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.118735Z","title":"Deformable image registration based on similarity-steered cnn regression","venue":null,"work_id":"708bec74-bdea-4d4d-ac09-639590796183","year":2017},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.858839Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:11d7689564a337573a9966a49065cc907e1f8e2d2ed833703f7ed5c0f6bc3d98","observation_id":"402b60a8-c6cb-4064-9362-c0944ad9d050","resolution":{"observed_at":"2026-08-14T14:43:07.124979Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.094445Z","title":"Large deformation diffeo- morphic metric mapping of vector fields","venue":null,"work_id":"a4975743-cae2-4fbf-bca4-87c01e0ab930","year":2005},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.863893Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:3899165811bae9810742505dd7937a5fc416017d2c9acacc89707939473f80df","observation_id":"a6a63bd2-7f27-47c8-87a7-737190ad920e","resolution":{"observed_at":"2026-08-14T14:43:07.100811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.073401Z","title":"Multi-contrast large deformation diffeomorphic metric mapping for diffusion tensor imaging","venue":null,"work_id":"a19cb743-1393-4079-8e57-69d54d81a9fd","year":2009},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.868147Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:91536d6d7263f9fe8aa69dc809c63ae2e75a3a7c9a3a4f22dcde3f7250679e54","observation_id":"d9125133-15ae-4f7b-9d49-611dd6c3a033","resolution":{"observed_at":"2026-08-14T14:43:07.080784Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:05.872385Z","title":"Infogan: Interpretable representation learning by information maximizing generative adversarial nets","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.872385Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:ef651566dae8e62dce453181e876e6967cee68953599e5d1a7f5d616fff66085","observation_id":"1597c6e9-ebd1-4973-8d94-ae4807be6e9e","resolution":{"observed_at":"2026-08-14T14:43:05.872385Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.047017Z","title":"Dagley et al","venue":null,"work_id":"8abe926d-c0e5-4ee5-bd3c-ea9ad8c992f9","year":2015},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.877222Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:20679148b0db35112050bfbdd5aad27d0d5396beadeea5fcc56805bbed1a8aae","observation_id":"94df1172-94ad-40bd-9bff-fbafcc3aa201","resolution":{"observed_at":"2026-08-14T14:43:07.053627Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.031424Z","title":"Dalca, G","venue":null,"work_id":"bed6a76a-0f40-4b86-aef9-aff5ee13aea9","year":2018},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.881710Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:19cc3ce709b053895236447fb2ddd45667996a84fd27736aa4ca7ebfeb03dbd7","observation_id":"6c067e87-a0cc-418d-85fa-a68d60ee4062","resolution":{"observed_at":"2026-08-14T14:43:07.036807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:07.012058Z","title":"Dalca, G","venue":null,"work_id":"81361bb3-d9cf-4bff-b6ba-2831caf62a93","year":2019},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.885844Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:56ecb9cc59c2592b069a1c5d866ed22f19ec93bde82e115477329eccbcbb5a86","observation_id":"00fe370a-9400-42cc-9e2d-5fbbd87e004a","resolution":{"observed_at":"2026-08-14T14:43:07.018125Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.990507Z","title":"Dalca et al","venue":null,"work_id":"03a75a9b-5a5f-4c96-a25d-3a3a90846202","year":2016},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.890047Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:6b8ac3a02966d616ff027d3d1b9e3f4040a23372d813943b0e91b3798d34940b","observation_id":"f49d4c3d-a3cb-4cdb-b121-a3d2171e7d85","resolution":{"observed_at":"2026-08-14T14:43:06.997008Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.973602Z","title":"Dalca, J","venue":null,"work_id":"dabbdc90-38b6-4c41-9882-2f914a524e9e","year":2018},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.896225Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:fe4b45cd099cf587aa1074e78b677cf2dbd95f8d164f4b9dd81b7737f917f226","observation_id":"fb43eaf6-eef8-4ca8-82f8-28afc2a16f56","resolution":{"observed_at":"2026-08-14T14:43:06.978502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.957793Z","title":"Large deformation minimum mean squared error template estimation for computational anatomy","venue":null,"work_id":"af2623a4-4604-45de-8100-255619ea6505","year":2004},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.900482Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:db7ef5cb1e3ebcc698d4e21abdda16d0bf28e6bebd0a5d02ad0919ef2a61a0da","observation_id":"7d64b65a-4942-4b0c-bb3d-d92ffb910ebb","resolution":{"observed_at":"2026-08-14T14:43:06.963036Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.939572Z","title":"Population shape regression from random design data","venue":null,"work_id":"a7e6d8a1-3d4a-46b5-b49b-99c68c5be60a","year":2010},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.904646Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:648b0e4cf82a97bb747cbd254f5024ebd6adfe9c272acba5b31f22ba27f8e18b","observation_id":"4274f947-8a02-46ea-baf6-4c258122e508","resolution":{"observed_at":"2026-08-14T14:43:06.947171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.924848Z","title":"de V os et al","venue":null,"work_id":"50d2c2bf-8f5f-45e4-a0f0-f4826be687cf","year":2017},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.908890Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:b24bf9644c414eb9b6dea91aa4053c635d9b7d8f9d65ffdea6b0e446f8c42005","observation_id":"8994d73b-0ef5-4ff5-8af0-9eb70934e07f","resolution":{"observed_at":"2026-08-14T14:43:06.930216Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.901869Z","title":"Di Martino et al","venue":null,"work_id":"e23546dd-3511-4b71-a0a2-9ff04aa61a05","year":2014},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.912321Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:46cde6c09e61052f3b736e2cd533f1ed500dae8ba24fef2d3196178aff5dfa31","observation_id":"cd9808e2-2bcd-49eb-b5f3-85533202e83b","resolution":{"observed_at":"2026-08-14T14:43:06.909707Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.883498Z","title":"Dosovitskiy et al","venue":null,"work_id":"221010a6-06e4-4dc1-906d-0cbae54b32d4","year":2015},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.916294Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:8ba69dc5fe7f39b93c35e308ff48af866ccae2162abc752ceba5749ead842368","observation_id":"aa8b0b11-f106-43ca-ac16-dd659a8493af","resolution":{"observed_at":"2026-08-14T14:43:06.888212Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.868739Z","title":"Hierarchical matching of deformable shapes","venue":null,"work_id":"151fd5eb-4f0e-4aee-b3f6-b0febefa20f6","year":2007},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.919979Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:f3184b67bb7dbfa0380cda78a9709ac7fa3d8771da34b91727bd69969f1ad240","observation_id":"72d4ceac-4865-484b-9adf-20f0a545ee2a","resolution":{"observed_at":"2026-08-14T14:43:06.874368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.855307Z","title":null,"venue":null,"work_id":"1e55a564-b009-4a70-a9dd-aad375afef64","year":2012},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.923677Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:6883e97ef36c0d4cf9cb27f953b42293bcea27869d84124ad828247fc856010d","observation_id":"c84d6da1-daa2-400d-ad4e-7bc7c7a4a860","resolution":{"observed_at":"2026-08-14T14:43:06.859777Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.838324Z","title":"Dense image registration through mrfs and efficient linear programming","venue":null,"work_id":"0a328384-eb05-4fc4-bf15-dbe3d0492c94","year":2008},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.927622Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:e8b94e570124e5f1230222c9a8f91823063043a6ac7f846ef8314338256bbded","observation_id":"47e7a964-d4bb-42d8-81fb-94259578ee50","resolution":{"observed_at":"2026-08-14T14:43:06.843272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.822258Z","title":"Gollub et al","venue":null,"work_id":"29f24b2f-7899-471f-a30d-22de61d3caa8","year":2013},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.931929Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:3cf1a47d43ddaeeea235d9782b642b8eb32f9ff80f668c563e61257c6b86e177","observation_id":"065136ef-c25d-4741-9d03-9b3181d52818","resolution":{"observed_at":"2026-08-14T14:43:06.827877Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:05.935328Z","title":"Deep learning","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.935328Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:0dd6a1ab01b1770229dc64f8bf98d4459fa364ea46d362b49dfd90306dc4727b","observation_id":"bfc958ba-cf02-41aa-88bd-d7df3540349f","resolution":{"observed_at":"2026-08-14T14:43:05.935328Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.795277Z","title":"A spatio-temporal atlas of the human fetal brain with application to tissue seg- mentation","venue":null,"work_id":"09e90adb-b1b2-4ebd-b90a-ee3cacff4f70","year":2009},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.938521Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:6e437e6ef1750aa3fef81b5f0add61fabc6e4319ba3d67b3f40a306d3822fa04","observation_id":"4530812c-5137-401b-a271-a571e5a6cec2","resolution":{"observed_at":"2026-08-14T14:43:06.800606Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.778029Z","title":"Registration of anatomical images using paths of diffeomorphisms parameterized with stationary vector field flows","venue":null,"work_id":"37a34a2a-4bf0-4bd5-8a2b-dd86ee7800c0","year":2009},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.943292Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:5da50b74635085dcfcea9d9b390b140a5127161c8cc679d8d432f2aa36984928","observation_id":"51972bb8-b4fd-4a5d-8e14-727dc608a64c","resolution":{"observed_at":"2026-08-14T14:43:06.784819Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.757593Z","title":"beta-vae: Learning basic visual concepts with a constrained variational framework","venue":null,"work_id":"d276a456-1d9a-4154-bb12-76f446226c2c","year":2017},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.947618Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:fc69c5c1cdc97c005ab7df98e11006c4ce5eabe014bc5d7e5a5c004f5b2d89c2","observation_id":"5a3e678c-508e-4e89-b6be-cf453362e2f3","resolution":{"observed_at":"2026-08-14T14:43:06.764360Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.737999Z","title":"J Holmes et al","venue":null,"work_id":"aa4899fb-1316-4d24-8496-e03c7ccc27e8","year":2015},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.951719Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:19e5d86fd63b4f16c7086500cfdb404d7abdf200ded226f0f6c4af2cb61a9ee2","observation_id":"39129384-cf6c-410a-b8f5-e75f0f170693","resolution":{"observed_at":"2026-08-14T14:43:06.742706Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.719001Z","title":"Horn and Brian G","venue":null,"work_id":"3104a6c8-f0b3-440a-ab76-8dd8ebb9ffee","year":1980},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.955412Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:4e7890034cafa3812a55c721e663bde05fdd48cec4bba56ff13b02ef22165a2a","observation_id":"1c53e4b0-6c65-4a9b-823c-e8462f6b041e","resolution":{"observed_at":"2026-08-14T14:43:06.725537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.704911Z","title":"Flownet 2.0: Evolution of optical flow estimation with deep networks","venue":null,"work_id":"f332957a-8029-4884-8272-b8cf36f80feb","year":2017},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.961313Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:ba2f299ffb37ba38c915af32a1a126a457b94a92c2a22123c300fa3cd02daaab","observation_id":"e7c3c478-2689-428c-8f7d-6e7010f659b2","resolution":{"observed_at":"2026-08-14T14:43:06.710883Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.689795Z","title":"Jain, Yu Zhong, and Sridhar Lakshmanan","venue":null,"work_id":"50f308a9-3a40-4d7f-a64d-66f6414119e5","year":1996},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.965635Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:9e8b4d9b38eaed2e1dcf300c39ffafaa0ceb16ecaccdf4cea8864202e8e2cde0","observation_id":"3c1eb859-e1f0-4a95-a5c0-678bac0645ad","resolution":{"observed_at":"2026-08-14T14:43:06.694891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.674105Z","title":"Back to basics: Unsupervised learn- ing of optical flow via brightness constancy and motion smoothness","venue":null,"work_id":"29209054-6441-4568-9242-c67856f5b81c","year":null},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.970012Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:ca1b6e4272322a3be836ad63d68dd7a10a7150e67a86fafcce58b152b8c00ac2","observation_id":"ddef89f3-2aa1-46bc-9580-a99ea21c4b86","resolution":{"observed_at":"2026-08-14T14:43:06.678269Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.658560Z","title":"The quick, draw!-ai experiment","venue":null,"work_id":"0b9865f2-418a-4619-bfdb-95f4efd9c113","year":2018},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.975208Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:2febacd122ca4f3ba7e954dd05c1d9e3a0dd47fdd14723d34070c140ae23b760","observation_id":"4762a43b-5e5e-48bb-a8e2-de07b3526926","resolution":{"observed_at":"2026-08-14T14:43:06.663177Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.645131Z","title":"Unbiased diffeomorphic atlas construction for computational anatomy","venue":null,"work_id":"727f3b9e-22c6-4912-ab3d-aee0c0b3236e","year":2004},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.980820Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:bd817e15ca05865ddd7e65172272cca7c4724584ecd0f9c36f5c928cbaa8fd14","observation_id":"a2fafaec-e193-4127-924f-15e541ba5bd5","resolution":{"observed_at":"2026-08-14T14:43:06.650041Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.631286Z","title":"Landmark matching via large deformation diffeomor- phisms","venue":null,"work_id":"343d6588-ab83-4f21-b21e-4ee9e274efc2","year":2000},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.985681Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:1255a060e5b1df9b3f772f4e774f4b4870ff26363fc15adbbbf78fef4016fe9d","observation_id":"d1c0e12d-5505-4819-9446-9139e6eb1301","resolution":{"observed_at":"2026-08-14T14:43:06.635712Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.618519Z","title":"Deformable spatial pyramid matching for fast dense correspondences","venue":null,"work_id":"6e15f332-f057-44e2-acaf-96236d031a8a","year":2013},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.990180Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:3846081896e91b4bf4e2900a4699386fe54ea9a76322d00a374248ad235cb2f4","observation_id":"588bd62c-682f-446b-8a37-cb6ffb6a7ac6","resolution":{"observed_at":"2026-08-14T14:43:06.622469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:05.994411Z","title":"Kingma and M","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.994411Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:938fe77c668505f5e81499326582d5eed7b11674e50184dc6ee16ba153ac3702","observation_id":"c3487c30-48a9-47ad-b948-585d99430ec5","resolution":{"observed_at":"2026-08-14T14:43:05.994411Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.595830Z","title":"Intrinsic shape context descriptors for deformable shapes","venue":null,"work_id":"b6a8e578-9d44-4ddc-887f-b51ddc7dff7b","year":2012},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:05.999009Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:06bbea7a47713242f3d8704a4b8946426f3ef862c7aea886a3a0204f6eda1597","observation_id":"fd8147f9-cc56-4f2e-91b0-fce2dccc5676","resolution":{"observed_at":"2026-08-14T14:43:06.600776Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.582422Z","title":"Krebs, T","venue":null,"work_id":"a4b00c36-c078-4cb5-8b72-1e5c09403d50","year":2018},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.002880Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:3ae1325edc599a3b7b4e9cf15323fe47e92c78df31c5367ae0ba1cddac55e274","observation_id":"24fec03a-bc7f-44a6-b0c7-008090163a77","resolution":{"observed_at":"2026-08-14T14:43:06.586573Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.006718Z","title":"Learn- ing a probabilistic model for diffeomorphic registration","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.006718Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:473b8fac103c171bb3702bbe659ba57deb5e603aee71c82bf45bc6dd81c01841","observation_id":"c741f1e3-00de-40b2-af4e-d35f971ec21d","resolution":{"observed_at":"2026-08-14T14:43:06.006718Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.560670Z","title":"Robust non-rigid registration through agent-based action learning","venue":null,"work_id":"2c49c4ba-a3ca-4eeb-bc56-ed6c2b714003","year":2017},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.010773Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:fb16b53c3b98a0b458a90dc1275e7f24110693055a8828cab21bf5751d9cbd56","observation_id":"95901dc8-4120-48ff-82a9-ef7b13ac0512","resolution":{"observed_at":"2026-08-14T14:43:06.565043Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.547438Z","title":"A dynamic 4d probabilistic atlas of the developing brain","venue":null,"work_id":"0bfcba27-843b-45ef-8b35-4cec5a5c3cea","year":2011},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.014998Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:61ec463e93822420af814b83c36740482339ea264ca99696f1fa4326d57fc5ff","observation_id":"0b8b9ed2-d015-46be-9c4c-6f101d0de81c","resolution":{"observed_at":"2026-08-14T14:43:06.551632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.018901Z","title":"The mnist database of handwritten digits","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.018901Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:d790d6c96e984bcc1c8ba7257c5b22b9dd5928dff5b363856a67d5c37fe4e3c6","observation_id":"4b204533-025c-4d53-891e-15185651c8ad","resolution":{"observed_at":"2026-08-14T14:43:06.018901Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.527083Z","title":"Bayesian template estimation in computational anatomy","venue":null,"work_id":"c40f5cda-9a64-4118-86ae-c8cfe96dc374","year":2008},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.023052Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:5995dc5b0ad28ee5e9709c001a9f6870b790858f37022276116d168455f8e677","observation_id":"44caa6c3-b57e-465b-98b6-8a95abeeba3b","resolution":{"observed_at":"2026-08-14T14:43:06.531331Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.05644","last_updated":"2016-05-25T00:17:45Z","snapshot_observed_at":"2026-08-14T22:22:29.258335Z","submitted_at":"2015-11-18T02:32:39Z","title":"Adversarial Autoencoders","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.05644","snapshot_observed_at":"2026-08-14T14:43:06.026961Z","title":"Adver- sarial autoencoders","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.026961Z"},"links":{"cited_paper":"/paper/1511.05644","citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:e144188a24f6afcd8d6ba3d6302712ff04c4b80b3c3b882b26c83f2a3655c71f","observation_id":"5b760a5d-6b5b-4641-a880-8ba8ddf48f57","resolution":{"observed_at":"2026-08-14T14:43:06.026961Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.513872Z","title":"Marcus et al","venue":null,"work_id":"70c8e78f-2d0d-4437-a8f1-f8e345cdd23c","year":2007},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.031587Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:829a19aa49477dfb0e0b7bf8ad8ec4a30cfc45cfb6aca06f8e8ff82a30b4ef8c","observation_id":"d34f35b6-a0c0-4a5f-9fd1-c3919b1bbb7c","resolution":{"observed_at":"2026-08-14T14:43:06.518113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.501257Z","title":"Marek et al","venue":null,"work_id":"4e6a3cfc-3f31-49c4-b329-1d0256c8dee7","year":2011},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.035779Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:6c8851eb80abe8006e9aed1065213f6addd4b9ba5db289f4f425ee627a441c6b","observation_id":"9930d595-7859-4ee7-8703-24748e0ce2f4","resolution":{"observed_at":"2026-08-14T14:43:06.505354Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.481843Z","title":"Milham et al","venue":null,"work_id":"9a4b0dc5-8875-4431-a3b7-7d2a64dda2de","year":2012},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.038883Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:74989ba6fe0578d6fd957df93b3d4b7b1c72436a8649a4c1d045143f34ced489","observation_id":"113a52c0-b60a-40af-95c6-0b2c492c53a6","resolution":{"observed_at":"2026-08-14T14:43:06.488325Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.469162Z","title":"Increasing the power of functional maps of the medial temporal lobe by using large deformation diffeomorphic metric mapping","venue":null,"work_id":"f32cb16b-05b4-4f0b-a261-f8f5dd37e690","year":2005},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.042439Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:2f40599264f02635ae917d3f4428fca3c63c0388d0b196c32ec02ba1a19f476b","observation_id":"edc5f5de-8868-45f1-bdd9-902934fa5a34","resolution":{"observed_at":"2026-08-14T14:43:06.473369Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.454977Z","title":"Modat, I.J.A","venue":null,"work_id":"c65fc7a7-278b-425c-bee9-58e47658e28d","year":2014},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.046797Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:764fac648840abce74a5af2f5d2a4006382767a2b4d0ea7189c5995fd206b637","observation_id":"07b8694e-7245-4278-8cbf-c3db04cfc5d7","resolution":{"observed_at":"2026-08-14T14:43:06.459319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.436028Z","title":"Parametric non-rigid registration using a stationary velocity field","venue":null,"work_id":"246c48fa-d386-49ba-9242-e651f5aa55cd","year":2012},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.051041Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:8c8ec15dabc7b803c4cd088a4d05b66b954a533eac1804327850bda72e93cb1c","observation_id":"1874de7c-a66f-4e0f-8d35-561118e86407","resolution":{"observed_at":"2026-08-14T14:43:06.440942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.423300Z","title":"Mueller et al","venue":null,"work_id":"511fa6a7-73db-48ec-b6f3-95b6a00c558a","year":2005},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.055705Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:2a7f00a680cae3af4ad3fb961034c2a3a06adcbd47082ab3a7509cc7b48740d1","observation_id":"e7a742f2-f3b1-42b3-aea7-5479caaaf9a4","resolution":{"observed_at":"2026-08-14T14:43:06.428329Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.410412Z","title":"Atlas-based whole brain white matter analysis using large deformation diffeomorphic metric mapping: application to normal elderly and alzheimer’s disease participants","venue":null,"work_id":"dc5d09a3-ddda-48fb-beef-fd0ff6613d9b","year":2009},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.059675Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:7bb2f41661c8306c58f478af4d04f67f2a84dfc5505ab984dc325119becc3924","observation_id":"77489fb7-7981-447b-9b3f-274c9b663f29","resolution":{"observed_at":"2026-08-14T14:43:06.415262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.394805Z","title":"Optical flow estimation using a spatial pyramid network","venue":null,"work_id":"537584f2-cd20-4c35-beb2-9805d5293778","year":2017},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.064263Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:9c55ba4fdc21ff786dd487a36e3892895f9a90e266d2988b00d88b7bdb1f540b","observation_id":"d9ce6c7c-b936-4c9f-9e37-623532b3cfc9","resolution":{"observed_at":"2026-08-14T14:43:06.400760Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.381299Z","title":"Rohé et al","venue":null,"work_id":"481f960a-d03c-47f8-93fa-7316163bb544","year":2017},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.069838Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:b1a645069c2c901cfc60d3065cb0c66ef0712d67680d51c8019d9f1cda51ead4","observation_id":"7e6c260e-5f68-48da-9555-c8054f6043f0","resolution":{"observed_at":"2026-08-14T14:43:06.385718Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.362988Z","title":"Ronneberger et al","venue":null,"work_id":"943c27f5-6b14-4f45-a843-efe703ec341f","year":2015},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.074474Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:2e380415c0ac0bb1d4862311811484dacac7b44453880c353889e83c6fa40233","observation_id":"b83a1a06-e025-445d-befc-11857739dbb9","resolution":{"observed_at":"2026-08-14T14:43:06.367987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.347881Z","title":"Image-driven popula- tion analysis through mixture modeling","venue":null,"work_id":"2f2062cd-b161-4984-a6c4-244d4d40ba24","year":2009},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.080143Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:a9ed43e6fdd51a708127485b230cbd5ee41a1686e8cc3b8309d6c2421d69314a","observation_id":"13b4abf6-d13a-4ab6-90a0-293955e5fbca","resolution":{"observed_at":"2026-08-14T14:43:06.352877Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.333335Z","title":"Sokooti et al","venue":null,"work_id":"916e971f-c721-4027-a04d-55b380c5b381","year":2017},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.085899Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:df5af4bb1ff9b2e8b16747e2b965cb59ca18b50663d3b521762f6aa22205b256","observation_id":"8eabafa1-d04b-41de-a685-e0b189fc902d","resolution":{"observed_at":"2026-08-14T14:43:06.337808Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.319497Z","title":"Template deformation for point cloud fitting","venue":null,"work_id":"7c9ebd60-3dee-45cd-9a73-b57bb46c2bca","year":2006},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.089908Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:1e21be9e355f4a5e493b3cee634f57c2b7085079fef04e4980720ec3e5ed8c8a","observation_id":"36101607-e3d2-49ce-96d8-d80a8de8e5be","resolution":{"observed_at":"2026-08-14T14:43:06.323829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.305057Z","title":"Sun et al","venue":null,"work_id":"367f0900-0fa9-47c6-a3d7-58b7f13d5bfc","year":2010},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.093984Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:ef0f036887d71cebba8e01bf89cb253336f074c5132d0b8f16ae36069e61702a","observation_id":"7de0a5a7-82f6-44b9-86a6-3b899ee799b4","resolution":{"observed_at":"2026-08-14T14:43:06.309971Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.290188Z","title":null,"venue":null,"work_id":"0c9eea32-2c84-47b1-9bb4-3840e281aafe","year":1998},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.098892Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:a91c3d684df8019f8346d37adfe8cadd46e5ca0609e88c686484d2c45ecb1898","observation_id":"917fe3b3-b9cd-44a1-9027-14c3acf8dcc6","resolution":{"observed_at":"2026-08-14T14:43:06.294564Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.271630Z","title":"Deep end2end voxel2voxel prediction","venue":null,"work_id":"ca172fd2-bddc-45ad-9668-1b9da3dde733","year":2016},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.103484Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:09d1e79a2b675b81000997e47cba50a4dd3975058cd1d1573a7d7f4e3d4368c8","observation_id":"c96e5921-7aa2-427d-b720-59c21a115351","resolution":{"observed_at":"2026-08-14T14:43:06.278536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.255099Z","title":"Diffeomorphic demons: Efficient non-parametric image registration","venue":null,"work_id":"06282d2e-b1c7-437c-804b-141e50ac8912","year":2009},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.109394Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:bfe8cab59c978a1448bc0d10f3e2b2d63f7dbbd9d78c4fac434f44be3b63564f","observation_id":"f9d0379e-3579-4730-83cb-ec5273c381b1","resolution":{"observed_at":"2026-08-14T14:43:06.260335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.237918Z","title":"Yang et al","venue":null,"work_id":"81116ee1-0571-4e31-9f4b-bb5881528180","year":2017},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.114125Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:e3bdd3ae875161e6a75db139f76b58dfe9f9e1de77b54e9301738d7c99211417","observation_id":"30cb7683-6e69-416b-a2c6-9ff6db7c6caf","resolution":{"observed_at":"2026-08-14T14:43:06.243241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.225455Z","title":"Learning task-optimal registration cost functions for localizing cytoarchitecture and function in the cerebral cortex","venue":null,"work_id":"fdc74975-defa-4c2b-af06-c81442bca0b4","year":2010},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.118276Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:b02e98968cc35896c14bbce819d29cb679bc9808cbae00b9f4a11b32d466c55b","observation_id":"3f20f04b-ab67-4663-adc5-ccef064dfb88","resolution":{"observed_at":"2026-08-14T14:43:06.229508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.209800Z","title":"Automated evaluation of physical therapy exercises using multi-template dynamic time warping on wearable sensor signals","venue":null,"work_id":"29bf4110-9d24-4630-9793-cd52a4493003","year":2014},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.121902Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:5c83f8af2b43e7b7c0409734b2f8eab21101c96d1869ae0b0a01f35d9635b7eb","observation_id":"87600b07-53d4-4761-98bf-87c2e0bab05a","resolution":{"observed_at":"2026-08-14T14:43:06.215197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:43:06.194512Z","title":"Zhang et al","venue":null,"work_id":"52d0cd93-f7e4-4189-8833-3b49215235ef","year":2017},"citing_paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks","version":2},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-14T14:43:06.126218Z"},"links":{"citing_paper":"/paper/1908.02738"},"observation_digest":"sha256:cefe302bac58c541833523bf4e6024045d5a673b7691c699252fe5e596b7b69d","observation_id":"e768b27b-7aa8-4e98-b3c3-a33ae97291cc","resolution":{"observed_at":"2026-08-14T14:43:06.200361Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.02738","last_updated":"2019-10-11T16:04:22Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T15:35:18.994312Z","submitted_at":"2019-08-07T17:29:36Z","title":"Learning Conditional Deformable Templates with Convolutional Networks"},"reference_resolution":{"displayed":73,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":10,"verified_exact":0,"verified_fuzzy":63},"total_outbound_references":73},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 73 of 73 outbound references and 0 inbound Pith citation observations for arXiv:1908.02738."}