{"as_of":"2026-08-15T01:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0008f5da7d76dc0b5ec4bab9602e3ae1099374ad801f922afb17e0020b53b824","coverage":[{"denominator":56,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":56,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T15:23:18.466580Z","state":"measured"},{"denominator":57,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":57,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-08T14:18:19.330577Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-11T18:41:12.099533Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"cited_work":{"arxiv_id":"2411.14332","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.14332","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Continuous nonlinear adaptive experimental design with gradient flow.arXiv preprint arXiv:2411.14332","venue":null,"work_id":"633580ed-d9ef-4f33-ab40-bda489fab66d","year":null},"citing_paper":{"arxiv_id":"2604.21849","last_updated":"2026-04-23T16:40:11Z","snapshot_observed_at":"2026-08-13T11:23:02.274744Z","submitted_at":"2026-04-23T16:40:11Z","title":"Beyond Expected Information Gain: Stable Bayesian Optimal Experimental Design with Integral Probability Metrics and Plug-and-Play Extensions","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-08T14:18:19.330577Z"},"links":{"cited_paper":"/paper/2411.14332","citing_paper":"/paper/2604.21849"},"observation_digest":"sha256:13f258c5e0e4ed831ef3439e770085a0875e9ad5b758d538fb7d2153afb06681","observation_id":"a109ed88-5f16-4168-9ad8-d18bf875e3c1","resolution":{"observed_at":"2026-05-11T18:41:12.106807Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2411.14332/citation-record","integrity":"/paper/2411.14332/integrity","json":"/paper/2411.14332/citation-record.json","paper":"/paper/2411.14332"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T15:23:21.128376Z","title":"Optimal experimental design for infi nite-dimensional bayesian inverse problems governed by pdes: A review","venue":null,"work_id":"ae0355e8-fba5-4308-98fc-1bf5ee8b0a53","year":2021},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:17.942210Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:ad0f823b2241b997742b53177fef33d94248e77d8de1094f9608276ab83824ec","observation_id":"e18f1732-0d29-49c5-93fd-fd073ef3d90d","resolution":{"observed_at":"2026-08-12T15:23:21.144524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:21.084017Z","title":"A-optimal design of experiments for infinite-dimensional bayesian li near inverse prob- lems with regularized ℓ0-sparsification","venue":null,"work_id":"98c299d4-5f8c-4b3a-8c56-b1bcb65b0352","year":2014},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:17.955774Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:f3a54fcf2bdc2d99164a866431eb7d7166c675070c2411d19f324d3de895024b","observation_id":"2cf9a936-1569-42e5-9b29-7ce6dd8671e0","resolution":{"observed_at":"2026-08-12T15:23:21.098310Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:21.025824Z","title":"A fast and scalable method for a-optimal design of experiments for infinite-dimensional bayesian nonlinear inverse problems","venue":null,"work_id":"30cfda58-f04b-47d6-84ed-a4d8624715d8","year":2016},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:17.964688Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:3383eebe16f2d98870dc7cc8baf977e44ef1badf2b9c1a439f1cf85341d2f800","observation_id":"4ad659e2-39de-4a55-bbd5-ec1b0eb71b05","resolution":{"observed_at":"2026-08-12T15:23:21.051732Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.970953Z","title":"E fficient d-optimal design of exper- iments for infinite-dimensional bayesian linear inverse pr oblems","venue":null,"work_id":"ba4c561e-c491-4b61-887b-fd013b3eb924","year":2018},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:17.971128Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:3011b1eb10b647c38a7957b86af332021f6474caf80e99f6208af53cf6edea80","observation_id":"f6759895-5daa-4465-bade-2ab25b847504","resolution":{"observed_at":"2026-08-12T15:23:20.982065Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.935278Z","title":"Gradient flows: in metric spaces and in the space of probability measures","venue":null,"work_id":"3a90effc-1f34-4735-ac86-b58ffffc6f28","year":2005},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:17.980908Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:57e1cdac3b8c335159b18595459e5c1b952efff34a139c365bc906f3305bec72","observation_id":"0872e9e5-969e-41ee-93ae-6a314097766a","resolution":{"observed_at":"2026-08-12T15:23:20.947982Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.897580Z","title":"Introduction to optimum design","venue":null,"work_id":"19e73fa0-4286-4631-a754-47a2ecdedf1e","year":2004},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:17.989960Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:d08e360d5ccd6d1c70b09d8e4b8cb09895f0db0e0d8d45c5abe13b056022bb5c","observation_id":"b9396e20-9f4d-490b-8356-efcb969d1846","resolution":{"observed_at":"2026-08-12T15:23:20.908742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.866354Z","title":"Gone fish- ing: Neural active learning with fisher embeddings","venue":null,"work_id":"930aaaf8-c385-4c44-bf92-da7c189230d1","year":2021},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:17.998607Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:2195e5ad7b8926870bf18f136b62cc8b4694835a1a9cfa62b598eec2688349ca","observation_id":"5483e881-3020-4e9c-9121-4dcd6ce8f90f","resolution":{"observed_at":"2026-08-12T15:23:20.874247Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.828180Z","title":"Go al-oriented optimal design of experiments for large-scale bayesian linear inve rse problems","venue":null,"work_id":"9eb37381-a49e-4d04-b706-511ad6581011","year":2018},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.007115Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:cecc4175dbfa70ac125622f290e926f5ebbabd50f025be3ad3db78df5804f581","observation_id":"108221a4-e625-4dc7-a80d-6e7e5d8d3788","resolution":{"observed_at":"2026-08-12T15:23:20.835348Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.790400Z","title":"Optimal and e fficient designs of experiments","venue":null,"work_id":"dcf4d7ee-c7bf-40e0-b29b-a97f34f4120b","year":1969},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.017532Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:ed169517c4a38d9bff346a98418307bc2901e9317c4803a42264478d15fb357f","observation_id":"4316a945-53d9-4ad0-8246-679627b6ccf5","resolution":{"observed_at":"2026-08-12T15:23:20.801620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.746752Z","title":"Active perception","venue":null,"work_id":"7b930b14-0925-4688-869a-bf293d33df86","year":1988},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.027821Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:285438da412043245cb241be71b26b32de68442ce15acac4674db5e0bbe56fa5","observation_id":"a9088a92-e8c8-4256-aa96-06f14864e21a","resolution":{"observed_at":"2026-08-12T15:23:20.758342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.703922Z","title":"Schl¨ oder","venue":null,"work_id":"a146a7f5-6bed-43a0-8a5c-38dc67346447","year":2000},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.035659Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:3166500f65000a10b7fdb4060b8d35728fe226e36577fcb9c010608129c65ade","observation_id":"60871456-eb9b-4315-a483-a67f621fc1d8","resolution":{"observed_at":"2026-08-12T15:23:20.717707Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.675812Z","title":"Practic al considerations for optimal designs in clinical dose finding studies","venue":null,"work_id":"1313f812-df56-4cf9-a6ab-d2f9ff279be3","year":2010},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.043129Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:8544ac72d430bf6c21f42259f491c27ee0ad87c132596529494d1a48362739dd","observation_id":"de86e83f-3a11-45ee-aec3-8913e49e7836","resolution":{"observed_at":"2026-08-12T15:23:20.686236Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.626981Z","title":"Minimax bounds for activ e learning","venue":null,"work_id":"ae86b676-daf8-4b55-991c-87aa01886d0d","year":2008},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.052266Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:93453d86a99558fa81b65849ad1bda9a080c55091c1611bcdac51d6601b08efe","observation_id":"bc8f6ee3-f52f-4ac7-b44b-9bc39ac3baac","resolution":{"observed_at":"2026-08-12T15:23:20.640738Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.592867Z","title":"Bayesian Ex perimental Design: A Review","venue":null,"work_id":"65cdb074-e489-4589-af76-d2403be621c6","year":1995},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.058401Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:7c833ab22407da7bd39ba12e6da67bb21f0a2519ca75ea2bbec9c7ee86fd1fed","observation_id":"be6c2505-9b55-4647-9fbc-3b724f0fd765","resolution":{"observed_at":"2026-08-12T15:23:20.603770Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.551817Z","title":"Convergence rates of active learning for maximum likelihoo d estimation","venue":null,"work_id":"02a5ec3f-afc1-4cbc-9842-8df9dadb5aea","year":2015},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.066347Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:995fbe6a1634a22f23dbe67e03aeae4ef3a9e6e94d8a57d4bce4a969341b343b","observation_id":"40474129-4037-4df8-af8d-c5a3e38fa327","resolution":{"observed_at":"2026-08-12T15:23:20.560424Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.11365","last_updated":"2024-03-17T22:51:26Z","snapshot_observed_at":"2026-08-13T00:52:21.901051Z","submitted_at":"2024-03-17T22:51:26Z","title":"Determination of a Small Elliptical Anomaly in Electrical Impedance Tomography using Minimal Measurements","version":1},"cited_work":{"arxiv_id":"2403.11365","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.11365","snapshot_observed_at":"2026-08-12T15:23:18.993647Z","title":"Determination of a Small Elliptical Anomaly in Electrical Impedance Tomography using Minimal Measurements","venue":"math.NA","work_id":"c5d6fb63-b7b9-460d-bc01-aced4618cf83","year":2024},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.081838Z"},"links":{"cited_paper":"/paper/2403.11365","citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:4724a82fc53ea2423cd71151aa15a91bf38abdff4d2fa3fc2768ea248a73fbe3","observation_id":"159dcbdb-8551-4d3d-bcc7-cb04367557c0","resolution":{"observed_at":"2026-08-12T15:23:19.005223Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.519254Z","title":null,"venue":null,"work_id":"50af8317-a61e-4058-b177-8850e103fec0","year":2001},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.088557Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:c71aff2323985b737b4df48cf93a64355cd1271b734eb4421e495485b78c34e3","observation_id":"f8a34eac-ebfd-4f8c-9d00-d41618a560c9","resolution":{"observed_at":"2026-08-12T15:23:20.529855Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.473703Z","title":"Optimal Design for Nonlinear Response Models","venue":null,"work_id":"58acc7b3-abfc-49db-b2c0-608895e55cea","year":2013},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.099661Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:b2bceb30f536c48caded3143c626f1691809f08094f7a028ce290d65832b2cdb","observation_id":"60a7c539-e303-4bdb-83fb-952e8abc550b","resolution":{"observed_at":"2026-08-12T15:23:20.484111Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.403925Z","title":"Model-oriented design of experiments , vol- ume 125","venue":null,"work_id":"b4b8e2c3-cb57-4f54-966b-ee776940c27a","year":2012},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.112789Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:6ef913da0c7fbb23c88fd65647e07710840f572a0d9b3602c756fdbabf8918d1","observation_id":"8bcde8a9-1e71-4ee9-b765-45cf3f0c260e","resolution":{"observed_at":"2026-08-12T15:23:20.425047Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.362115Z","title":"Elsevier, 2013","venue":null,"work_id":"0e8035ab-e652-4fb8-9949-c7dc9d599296","year":2013},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.122462Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:cde7d7da423da399ee325f76453c73f0eb722c343611d7977dfb05a42f254934","observation_id":"f328921d-4112-46da-952f-21aa91889267","resolution":{"observed_at":"2026-08-12T15:23:20.369914Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.314164Z","title":"Figalli and F","venue":null,"work_id":"c7975818-b2c0-4d0c-b667-326b6d96b773","year":2021},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.129618Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:e37eadcb7ed8b5104e6a7a041bf2d5c82e977ccf4fe392ad5637c8e07c0b40b6","observation_id":"3780e3ba-694f-4fff-833d-9380fa45f18f","resolution":{"observed_at":"2026-08-12T15:23:20.321145Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.260282Z","title":"A unified stochastic gradient approach to design ing bayesian-optimal experiments","venue":null,"work_id":"b25e7fd5-24e3-4a0b-828f-2e7f4470d670","year":2020},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.139033Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:c4cdf3050e926af99d062be49400f74f6aa7ec15e380ae27267472b6fd6e40a6","observation_id":"9ced3507-c00a-4b05-a759-89ebfdcbf301","resolution":{"observed_at":"2026-08-12T15:23:20.279955Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.212361Z","title":"Deep Bayesian active learning with image data","venue":null,"work_id":"8216a847-a548-409c-b261-927583648a43","year":2017},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.149788Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:f82e80130f9412be6d7e26bd62ec8d595a2dda8f4bf8d1ed57ca0ea114d60b2e","observation_id":"bd4b1aba-7c78-4933-a1ed-b582e2910278","resolution":{"observed_at":"2026-08-12T15:23:20.229051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.144373Z","title":"Nea r-optimal bayesian ac- tive learning with noisy observations","venue":null,"work_id":"3f93b573-4b2d-475e-b421-dddb62882a2b","year":2010},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.160535Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:e2b8ce47e32daf2ee56489779b19f663ae8f41a015fbf640385b0895464f4c73","observation_id":"7c661ce9-db4c-4bfc-a756-cd107edcd5ba","resolution":{"observed_at":"2026-08-12T15:23:20.158374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.115215Z","title":"Introduction to quantum mechanics","venue":null,"work_id":"fb34ff25-94ba-4bcd-aa0f-229da080a20a","year":2018},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.167419Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:2bc2afae5f248a2a7d49bb4d199639f1edb72322fc870e81cfcbfa720a7c3cd1","observation_id":"9f08d198-3790-4faa-9e5a-24db42113fdb","resolution":{"observed_at":"2026-08-12T15:23:20.121372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.073657Z","title":"Numerical methods for e xperimental design of large-scale linear ill-posed inverse problems","venue":null,"work_id":"49ec6316-7f60-4ad3-91ff-1982a9133dcf","year":2008},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.178474Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:77ef5a5fdcbbeec657d993f9ff595dcad1e44a4886ecca19e97cc16470ba6679","observation_id":"2c3c712c-159e-4857-ab41-d232d10293e3","resolution":{"observed_at":"2026-08-12T15:23:20.081451Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.045733Z","title":"Numerical methods for t he design of large-scale nonlinear discrete ill-posed inverse problem s","venue":null,"work_id":"1ece4d5d-833c-428e-8081-7ed9a2b29813","year":2009},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.184450Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:9e5fd6235c329e78df96e425acce066d9a72a222d3167cfa54eaf4597415a5c9","observation_id":"35fb06b9-bd5f-4398-b450-5762d5f0bf4f","resolution":{"observed_at":"2026-08-12T15:23:20.052061Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:20.018600Z","title":"Numeri- cal methods for a-optimal designs with a sparsity constrain t for ill-posed inverse problems","venue":null,"work_id":"e19ff995-eb61-4190-8a01-3029d13a9dec","year":2012},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.197439Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:eee0ba52f5cdb54e5b2711bfbe40b6dee0e26e12752a91642031260407366007","observation_id":"d0aacc55-9a52-491c-9300-4ef659fd503e","resolution":{"observed_at":"2026-08-12T15:23:20.028747Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.979468Z","title":"Bayesian opti- mal designs for phase i clinical trials","venue":null,"work_id":"b223720b-6983-4d5c-be21-138f7eb6c530","year":2003},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.207189Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:1c4bffaaa545fc1b2d54ae622d0e0aa49a096bdc5f3048f192aeda57cd7ecaf3","observation_id":"a2a736c8-3e82-4dc5-8ed2-8a1ddf585e0e","resolution":{"observed_at":"2026-08-12T15:23:19.992863Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.948635Z","title":"Optimization with PDE Constraints, volume 23","venue":null,"work_id":"5d0ed140-6754-440b-aca8-209b266fe08e","year":2008},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.214197Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:b59df863370d9c089032e710f77e68172dc4b8625b7531728a9735417d857b0d","observation_id":"d1c8fccb-2e97-48fa-a136-caa735a0b2a1","resolution":{"observed_at":"2026-08-12T15:23:19.956444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1112.5745","last_updated":"2011-12-24T17:53:19Z","snapshot_observed_at":"2026-08-12T12:05:47.570397Z","submitted_at":"2011-12-24T17:53:19Z","title":"Bayesian Active Learning for Classification and Preference Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1112.5745","snapshot_observed_at":"2026-08-12T15:23:18.224297Z","title":"Bayesian active learning for classification and preference learning","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.224297Z"},"links":{"cited_paper":"/paper/1112.5745","citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:9ef4d6e687cb11f5d670fcbb3c32bbf2ca62005c150bda31c80c9da83d243809","observation_id":"fda39d5b-022b-4785-b8bb-238356773a81","resolution":{"observed_at":"2026-08-12T15:23:18.224297Z","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":"2026-08-12T15:23:19.905747Z","title":"Optima l experimental design: Formulations and computations","venue":null,"work_id":"25b7b024-11b1-47a9-8165-8362b52e0baf","year":2024},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.233204Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:618ad56b17c966e870a430ebca0980886f4774426c89109bca856bc6e486fb38","observation_id":"fa3c10bc-7ae5-40a7-abba-085194cc65f8","resolution":{"observed_at":"2026-08-12T15:23:19.918152Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.854875Z","title":"Simulation-based optim al bayesian ex- perimental design for nonlinear systems","venue":null,"work_id":"ed68257c-7c06-42fd-99b9-72ce3a70fdb7","year":2013},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.240142Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:82170ade9bba3ca1d59c46b9ff57414abe55c7e9c8fbffacef82bd784174c52d","observation_id":"c54819b5-9467-4da1-b712-09e140273c3b","resolution":{"observed_at":"2026-08-12T15:23:19.868845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.818613Z","title":"Gradient-based stochas tic optimization methods in bayesian experimental design","venue":null,"work_id":"c27dcba6-056a-4ba0-bcc1-431aded06d35","year":2014},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.245533Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:46b64d56b11595ee0c30dfdfd0b8ceca1988f2966067b285e24c5257c547e82a","observation_id":"0f417f26-439f-4acc-be1e-f3ccf19c09d3","resolution":{"observed_at":"2026-08-12T15:23:19.827852Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1604.08320","last_updated":"2016-04-28T06:32:27Z","snapshot_observed_at":"2026-08-14T21:59:45.543758Z","submitted_at":"2016-04-28T06:32:27Z","title":"Sequential Bayesian optimal experimental design via approximate dynamic programming","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1604.08320","snapshot_observed_at":"2026-08-12T15:23:18.253994Z","title":"Sequential bayesian opt imal ex- perimental design via approximate dynamic programming","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.253994Z"},"links":{"cited_paper":"/paper/1604.08320","citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:720483c8c3647d2d7d4d880b658eb01cbb8f38a6785b33b8f5941a1c18165054","observation_id":"c729561f-94f8-4232-886c-6f9b9591aef8","resolution":{"observed_at":"2026-08-12T15:23:18.253994Z","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":"2026-08-12T15:23:19.777558Z","title":"Batch gree dy maximization of non-submodular functions: Guarantees and applications to experimental design","venue":null,"work_id":"4fc3994a-948c-49df-96ab-ca206ea1ec83","year":2021},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.270227Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:bff343b9ca9c2470f60bc6587042357af21f42dbca0a35af8f27b0fa4bf289ba","observation_id":"9d214f84-af14-4dfa-84ed-deac5165f4a9","resolution":{"observed_at":"2026-08-12T15:23:19.792800Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2401.07806","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T15:23:18.829647Z","title":"Op timal experimental design for linear models via gradient flow","venue":null,"work_id":"19d96437-2e6d-4d0c-93ed-0e4f736a103b","year":2024},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.280616Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:54c59adbd453116c9d901fa779739577eca821f4358a9ccfa1f93d90bb459a4c","observation_id":"ed3979d7-2314-4b1c-8a2e-cef8f9a4d3d9","resolution":{"observed_at":"2026-08-12T15:23:18.848192Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.728476Z","title":"Optimal designs for mi xed continuous and binary responses with quantitative and qualitative factors","venue":null,"work_id":"673033d4-b7d7-41de-a7c6-cca65b642b38","year":2021},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.286902Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:7c6dcf80c6ed062dd237ca953eaa083e27a087e59e98f82501a10e7c760f073e","observation_id":"03bf3739-57f3-414c-9f2a-054ef54dc723","resolution":{"observed_at":"2026-08-12T15:23:19.751455Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.691564Z","title":null,"venue":null,"work_id":"6880628f-b575-4e94-8789-ade1ddf4bd3f","year":1974},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.296456Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:bab9911a77a9e5c4a9a28b6d6997c4379146ac9f253c0aedb99494b993366bfb","observation_id":"10e03dca-1c9b-4e29-8b19-b84e381380ca","resolution":{"observed_at":"2026-08-12T15:23:19.700308Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.643728Z","title":"Kiefer and J","venue":null,"work_id":"74178fa2-7c87-4b5a-a95d-cc32cd146135","year":1959},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.305532Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:304cb9823297bfafaa179d5d93f541a4d55d30819e6c657835b74c87871aaac1","observation_id":"1becc9d9-8cce-468d-acf4-602c305f46c5","resolution":{"observed_at":"2026-08-12T15:23:19.656553Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.601489Z","title":"An introduction to the mathematical th eory of inverse problems","venue":null,"work_id":"c87325a6-b438-4793-a245-cfb9036f1ba5","year":1996},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.318889Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:6abcd7c396c63330e263ff18cb7e4ae5ef9b5abc15c1c530ec7c72dcea3e638b","observation_id":"6f06ff49-f8a4-4b9e-8387-7b775dd4e284","resolution":{"observed_at":"2026-08-12T15:23:19.608009Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.562679Z","title":"The implicit function theorem: history, theory, and applications","venue":null,"work_id":"43d33a92-f813-46dc-876c-769f1cd47735","year":2002},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.325722Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:05ae32e73ff1b21a9e13e02656b04086ba5e38adbd124671b3ab012c378a9df5","observation_id":"ba137cd0-5b5f-4359-a532-682e340b0625","resolution":{"observed_at":"2026-08-12T15:23:19.573722Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.15053","last_updated":"2024-02-23T02:14:44Z","snapshot_observed_at":"2026-08-13T04:12:26.019996Z","submitted_at":"2024-02-23T02:14:44Z","title":"Nonlinear Bayesian optimal experimental design using logarithmic Sobolev inequalities","version":1},"cited_work":{"arxiv_id":"2402.15053","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.15053","snapshot_observed_at":"2026-08-12T15:23:18.662954Z","title":"Nonlinear Bayesian optimal experimental design using logarithmic Sobolev inequalities","venue":"stat.ML","work_id":"d3cc6ac9-480f-4215-a44b-a6f5f70d4e29","year":2024},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.350700Z"},"links":{"cited_paper":"/paper/2402.15053","citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:3a16da8ce21d7b7d413ec7b5f85ec00c02443a872fd2ed289e1aa67d015532a5","observation_id":"2770ed54-b57b-4de3-89f3-2967f6e4a4c8","resolution":{"observed_at":"2026-08-12T15:23:18.677657Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.494769Z","title":null,"venue":null,"work_id":"b5e69fa3-362c-4f6c-930b-1f699a1d6f12","year":1963},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.361174Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:11a4b9038c62792b6e2f606138e97b842f6c720edd3063226c2b915a3e1a0514","observation_id":"23937f9f-7c43-4930-a98f-ae57cfcd935f","resolution":{"observed_at":"2026-08-12T15:23:19.505453Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.454779Z","title":"Continuous-v ariable optical quantum-state tomography","venue":null,"work_id":"cc9a8ec2-181f-4118-9586-70d1fdd959aa","year":2009},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.371770Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:0ddffd5fefeb4154538091e69dbfc40bef40405cfd92cddd1e1446987ca33d29","observation_id":"b35ca5ad-2192-42d3-89ad-d6c4c9dc237e","resolution":{"observed_at":"2026-08-12T15:23:19.467431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.397115Z","title":"D-optimal","venue":null,"work_id":"5acad18b-ab0d-453f-9bec-84028c6f01b6","year":2000},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.377251Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:19e019a3f715dde67045f5cad7e4a77cc3b27e0af33a5ebf551c45090699ff23","observation_id":"01bdc154-e295-4f0e-96e4-91db476de458","resolution":{"observed_at":"2026-08-12T15:23:19.407262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.09283","last_updated":"2022-11-17T01:02:12Z","snapshot_observed_at":"2026-08-13T13:40:42.605829Z","submitted_at":"2022-11-17T01:02:12Z","title":"Active Learning with Expected Error Reduction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.09283","snapshot_observed_at":"2026-08-12T15:23:18.385518Z","title":"Active learning with expected error reduction","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.385518Z"},"links":{"cited_paper":"/paper/2211.09283","citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:8640bd24b51dccf61b25bcf47a3824ff5c8ac9a0284a366d862d71cb6feb88c3","observation_id":"e794d50d-e4a0-46c6-aee7-ba772b7aa5f0","resolution":{"observed_at":"2026-08-12T15:23:18.385518Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T15:23:18.392687Z","title":"Optimal Design of Experiments","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.392687Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:7cbb82ee0e50ceae580bad78f8af724c109bed7bca93d903362e8e05b60ce71f","observation_id":"de49349a-86b8-48c7-a3b4-92877c8d0d9e","resolution":{"observed_at":"2026-08-12T15:23:18.392687Z","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":"2026-08-12T15:23:19.315318Z","title":"Design and analysis of computer experiments","venue":null,"work_id":"c58d31bf-0b7e-40eb-ae4c-86eee106a768","year":1989},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.400786Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:d524039245123a1c8a6da712a260d5e26fc53592737337b9803375f1f26d4a7f","observation_id":"f2481dde-8503-4d92-ad99-e8fa079709b8","resolution":{"observed_at":"2026-08-12T15:23:19.322776Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.271128Z","title":"Optimal Transport for Applied Mathematicians: Calculus of V ariations, PDEs, and Modeling, volume 87","venue":null,"work_id":"765be669-ade3-44d5-beac-99146ccf6e44","year":2015},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.409979Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:c80dc773c30447a377cb5de1036533bff0facbaad5875dce6c6d6b72ee2d9ec7","observation_id":"dfcfbffc-bf59-4016-9add-44ba458e4582","resolution":{"observed_at":"2026-08-12T15:23:19.283837Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.217122Z","title":"Bayesian sequential optimal experimental design for linear regression with reinforcement learning","venue":null,"work_id":"618d9d2c-79ca-4887-be00-59e1018dbda3","year":2022},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.420170Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:5040deaae8575451c421dc1954034668590909d5d805bc1a141eff1e96e2b7da","observation_id":"b6f3f878-35db-44e4-beb9-ed966bd3b6a4","resolution":{"observed_at":"2026-08-12T15:23:19.223868Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1708.00489","last_updated":"2018-06-01T10:17:23Z","snapshot_observed_at":"2026-08-14T20:43:50.669164Z","submitted_at":"2017-08-01T19:50:53Z","title":"Active Learning for Convolutional Neural Networks: A Core-Set Approach","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.00489","snapshot_observed_at":"2026-08-12T15:23:18.427291Z","title":"Active learning for con volutional neural net- works: A core-set approach","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.427291Z"},"links":{"cited_paper":"/paper/1708.00489","citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:f60cbdfc425e28b5c501dae8eb9d736964d2658db029f31ff29862af7d74d0f4","observation_id":"f0239af1-f029-4923-97dd-3dd038ea4fe5","resolution":{"observed_at":"2026-08-12T15:23:18.427291Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T15:23:18.439177Z","title":"Active learning literature survey","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.439177Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:1b7c41fa773e2e22701c88d2f5f5c0fb05ad934d9ea218b0e69798a99c259352","observation_id":"7f96063b-abc5-49e5-9ae4-605ab3f26971","resolution":{"observed_at":"2026-08-12T15:23:18.439177Z","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":"2026-08-12T15:23:19.146736Z","title":"Inverse problem theory and methods for model parameter esti - mation","venue":null,"work_id":"da36fe6f-72ab-4fc5-b71c-c4c5cbd38e15","year":2005},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.447910Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:0e173925eb965bc46df8d14378e94ba2061fba4283340696fc0da5038971c5eb","observation_id":"f979f9c4-af64-487d-a06a-e3cf4194d03d","resolution":{"observed_at":"2026-08-12T15:23:19.156777Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.105763Z","title":"The sequential generation of d-optimum experimental designs","venue":null,"work_id":"0c14e4a9-aa04-4c63-b11b-e2dc93ba2885","year":1970},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.460019Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:1738d92d6e92c83fe94755b367494a55dbe6588a7f0568a761694dd4bba224bc","observation_id":"8c5d3e75-1cac-4987-8e5a-10a7fc200124","resolution":{"observed_at":"2026-08-12T15:23:19.114342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T15:23:19.054083Z","title":"Mastering quantum mechanics: essentials, theory, and appl i- cations","venue":null,"work_id":"46d1af41-a88f-47ec-a2d1-6eef35c0b69b","year":2022},"citing_paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-12T15:23:18.466580Z"},"links":{"citing_paper":"/paper/2411.14332"},"observation_digest":"sha256:25996207d7c1d6a269caf3c072d936663f76d214d76c62f65f3e9b8910356d3b","observation_id":"01d8940b-dd07-4784-b30b-262f3a95748a","resolution":{"observed_at":"2026-08-12T15:23:19.069825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.14332","last_updated":"2025-06-08T01:57:56Z","latest_version":2,"primary_category":"math.NA","snapshot_observed_at":"2026-08-13T15:12:43.215615Z","submitted_at":"2024-11-21T17:25:16Z","title":"Continuous nonlinear adaptive experimental design with gradient flow"},"reference_resolution":{"displayed":56,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":3,"verified_fuzzy":44},"total_outbound_references":56},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 1 inbound Pith citation observation for arXiv:2411.14332."}