{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:SXX6X6CG5COVL2KFCOJK4DSBCP","short_pith_number":"pith:SXX6X6CG","canonical_record":{"source":{"id":"2009.09878","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-09-21T13:57:10Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"122c09fe0b70891b2d38c6fe19168e9b7d881c499d04803cffd655b1be3ef6a6","abstract_canon_sha256":"9ca3896d75ce99f46c218bc99b29e63b64a3d7f1bfc1780a83ce7169fbc38a2b"},"schema_version":"1.0"},"canonical_sha256":"95efebf846e89d55e9451392ae0e4113e36bba52947742c43551179f9039748c","source":{"kind":"arxiv","id":"2009.09878","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.09878","created_at":"2026-07-05T01:36:53Z"},{"alias_kind":"arxiv_version","alias_value":"2009.09878v1","created_at":"2026-07-05T01:36:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.09878","created_at":"2026-07-05T01:36:53Z"},{"alias_kind":"pith_short_12","alias_value":"SXX6X6CG5COV","created_at":"2026-07-05T01:36:53Z"},{"alias_kind":"pith_short_16","alias_value":"SXX6X6CG5COVL2KF","created_at":"2026-07-05T01:36:53Z"},{"alias_kind":"pith_short_8","alias_value":"SXX6X6CG","created_at":"2026-07-05T01:36:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:SXX6X6CG5COVL2KFCOJK4DSBCP","target":"record","payload":{"canonical_record":{"source":{"id":"2009.09878","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-09-21T13:57:10Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"122c09fe0b70891b2d38c6fe19168e9b7d881c499d04803cffd655b1be3ef6a6","abstract_canon_sha256":"9ca3896d75ce99f46c218bc99b29e63b64a3d7f1bfc1780a83ce7169fbc38a2b"},"schema_version":"1.0"},"canonical_sha256":"95efebf846e89d55e9451392ae0e4113e36bba52947742c43551179f9039748c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:36:53.925177Z","signature_b64":"RoI185y7hMttVTLRNDavsOpOYotowSfQzMeDQOD/FPwWDWeShi2Vx3tcw/pVN1m4MctY3KqYk5DSy+Gf+evCCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"95efebf846e89d55e9451392ae0e4113e36bba52947742c43551179f9039748c","last_reissued_at":"2026-07-05T01:36:53.924835Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:36:53.924835Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2009.09878","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:36:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jQvy8M2q+CLkWZvXFpIg4bIxZoO0BTYIyhcU63ylcPJ9MQ0qd2QYiDqXFMR8yFUhEhPCFf5zjrdI6Q6CocrdDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T20:03:06.760626Z"},"content_sha256":"aa52c7bcf11ca9c36f2c3db07758cdfd8a7c022b717efb3d7f774d4b6d209195","schema_version":"1.0","event_id":"sha256:aa52c7bcf11ca9c36f2c3db07758cdfd8a7c022b717efb3d7f774d4b6d209195"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:SXX6X6CG5COVL2KFCOJK4DSBCP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Haar Wavelet based Block Autoregressive Flows for Trajectories","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Apratim Bhattacharyya, Bernt Schiele, Christoph-Nikolas Straehle, Mario Fritz","submitted_at":"2020-09-21T13:57:10Z","abstract_excerpt":"Prediction of trajectories such as that of pedestrians is crucial to the performance of autonomous agents. While previous works have leveraged conditional generative models like GANs and VAEs for learning the likely future trajectories, accurately modeling the dependency structure of these multimodal distributions, particularly over long time horizons remains challenging. Normalizing flow based generative models can model complex distributions admitting exact inference. These include variants with split coupling invertible transformations that are easier to parallelize compared to their autore"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.09878","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2009.09878/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:36:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gUpjrv3tKWJFyYn4Im4oQPcBzvWyDlrRmBJfHyDH/nqmcnMIhbOD8PVhEMeYV9kNuEbJAd6hE14YY/3zXcE5Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T20:03:06.761126Z"},"content_sha256":"0c56ee1a1170b7edef24a20aa8afdaa583417112c3c8254d84406250b4f9d91b","schema_version":"1.0","event_id":"sha256:0c56ee1a1170b7edef24a20aa8afdaa583417112c3c8254d84406250b4f9d91b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SXX6X6CG5COVL2KFCOJK4DSBCP/bundle.json","state_url":"https://pith.science/pith/SXX6X6CG5COVL2KFCOJK4DSBCP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SXX6X6CG5COVL2KFCOJK4DSBCP/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-19T20:03:06Z","links":{"resolver":"https://pith.science/pith/SXX6X6CG5COVL2KFCOJK4DSBCP","bundle":"https://pith.science/pith/SXX6X6CG5COVL2KFCOJK4DSBCP/bundle.json","state":"https://pith.science/pith/SXX6X6CG5COVL2KFCOJK4DSBCP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SXX6X6CG5COVL2KFCOJK4DSBCP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:SXX6X6CG5COVL2KFCOJK4DSBCP","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"9ca3896d75ce99f46c218bc99b29e63b64a3d7f1bfc1780a83ce7169fbc38a2b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-09-21T13:57:10Z","title_canon_sha256":"122c09fe0b70891b2d38c6fe19168e9b7d881c499d04803cffd655b1be3ef6a6"},"schema_version":"1.0","source":{"id":"2009.09878","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.09878","created_at":"2026-07-05T01:36:53Z"},{"alias_kind":"arxiv_version","alias_value":"2009.09878v1","created_at":"2026-07-05T01:36:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.09878","created_at":"2026-07-05T01:36:53Z"},{"alias_kind":"pith_short_12","alias_value":"SXX6X6CG5COV","created_at":"2026-07-05T01:36:53Z"},{"alias_kind":"pith_short_16","alias_value":"SXX6X6CG5COVL2KF","created_at":"2026-07-05T01:36:53Z"},{"alias_kind":"pith_short_8","alias_value":"SXX6X6CG","created_at":"2026-07-05T01:36:53Z"}],"graph_snapshots":[{"event_id":"sha256:0c56ee1a1170b7edef24a20aa8afdaa583417112c3c8254d84406250b4f9d91b","target":"graph","created_at":"2026-07-05T01:36:53Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2009.09878/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Prediction of trajectories such as that of pedestrians is crucial to the performance of autonomous agents. While previous works have leveraged conditional generative models like GANs and VAEs for learning the likely future trajectories, accurately modeling the dependency structure of these multimodal distributions, particularly over long time horizons remains challenging. Normalizing flow based generative models can model complex distributions admitting exact inference. These include variants with split coupling invertible transformations that are easier to parallelize compared to their autore","authors_text":"Apratim Bhattacharyya, Bernt Schiele, Christoph-Nikolas Straehle, Mario Fritz","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-09-21T13:57:10Z","title":"Haar Wavelet based Block Autoregressive Flows for Trajectories"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.09878","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:aa52c7bcf11ca9c36f2c3db07758cdfd8a7c022b717efb3d7f774d4b6d209195","target":"record","created_at":"2026-07-05T01:36:53Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"9ca3896d75ce99f46c218bc99b29e63b64a3d7f1bfc1780a83ce7169fbc38a2b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-09-21T13:57:10Z","title_canon_sha256":"122c09fe0b70891b2d38c6fe19168e9b7d881c499d04803cffd655b1be3ef6a6"},"schema_version":"1.0","source":{"id":"2009.09878","kind":"arxiv","version":1}},"canonical_sha256":"95efebf846e89d55e9451392ae0e4113e36bba52947742c43551179f9039748c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"95efebf846e89d55e9451392ae0e4113e36bba52947742c43551179f9039748c","first_computed_at":"2026-07-05T01:36:53.924835Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:36:53.924835Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RoI185y7hMttVTLRNDavsOpOYotowSfQzMeDQOD/FPwWDWeShi2Vx3tcw/pVN1m4MctY3KqYk5DSy+Gf+evCCw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:36:53.925177Z","signed_message":"canonical_sha256_bytes"},"source_id":"2009.09878","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aa52c7bcf11ca9c36f2c3db07758cdfd8a7c022b717efb3d7f774d4b6d209195","sha256:0c56ee1a1170b7edef24a20aa8afdaa583417112c3c8254d84406250b4f9d91b"],"state_sha256":"94e1d1c2b7e327db4bb3df99f3d39dfe62a68a7667ce769884dba27fdf6aacc2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fJQpBECSGM0f7ZkISRThtUkzDhQrBAiWa4TKeUW/65yEpVGCQQAU5AaIwqoE3p4ZBbnT/2czM4kB60zlnlJpBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T20:03:06.765630Z","bundle_sha256":"d735bee7690c0346b0433d8418cf07de9f19c26c34ee335a76c9b1b3df36fe0b"}}