{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:57GFFSIPDHIWUEHFB427MKWXZK","short_pith_number":"pith:57GFFSIP","canonical_record":{"source":{"id":"2210.04165","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-09T04:39:15Z","cross_cats_sorted":["cs.CE","nlin.CD","stat.ML"],"title_canon_sha256":"e7d4c9985f6b5a471a561e4dacfbdc6eb6b1a92e57350db5c5439a8c5be56cca","abstract_canon_sha256":"2156c3354b912418b69a7e1a7cfaeae44a6a4b51c4f26e0267838e8ccf2ca40c"},"schema_version":"1.0"},"canonical_sha256":"efcc52c90f19d16a10e50f35f62ad7caa98bf762f0e35efcdd359d4241a3f645","source":{"kind":"arxiv","id":"2210.04165","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.04165","created_at":"2026-07-05T06:26:42Z"},{"alias_kind":"arxiv_version","alias_value":"2210.04165v2","created_at":"2026-07-05T06:26:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.04165","created_at":"2026-07-05T06:26:42Z"},{"alias_kind":"pith_short_12","alias_value":"57GFFSIPDHIW","created_at":"2026-07-05T06:26:42Z"},{"alias_kind":"pith_short_16","alias_value":"57GFFSIPDHIWUEHF","created_at":"2026-07-05T06:26:42Z"},{"alias_kind":"pith_short_8","alias_value":"57GFFSIP","created_at":"2026-07-05T06:26:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:57GFFSIPDHIWUEHFB427MKWXZK","target":"record","payload":{"canonical_record":{"source":{"id":"2210.04165","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-09T04:39:15Z","cross_cats_sorted":["cs.CE","nlin.CD","stat.ML"],"title_canon_sha256":"e7d4c9985f6b5a471a561e4dacfbdc6eb6b1a92e57350db5c5439a8c5be56cca","abstract_canon_sha256":"2156c3354b912418b69a7e1a7cfaeae44a6a4b51c4f26e0267838e8ccf2ca40c"},"schema_version":"1.0"},"canonical_sha256":"efcc52c90f19d16a10e50f35f62ad7caa98bf762f0e35efcdd359d4241a3f645","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:26:42.952210Z","signature_b64":"XY7iHW+JiZnbNH3iu9Cbf8k5inrcwg/YQlj9jbvJJx5nWT2771xh3xjDKgQsSk2sy3lBtIlIFYywonuATM/eBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"efcc52c90f19d16a10e50f35f62ad7caa98bf762f0e35efcdd359d4241a3f645","last_reissued_at":"2026-07-05T06:26:42.951716Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:26:42.951716Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.04165","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:26:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aOYemBOlEnyQYf6JOzBfJD9+g1ndxONzH6GMTjWDK1DmQWYr79RQ6L9/LA+P1OYwwXDgaHNIek88QMNuQUKBBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T18:36:56.071418Z"},"content_sha256":"369176d5bf8cb7196c33795825a9c1e94cd61d113e9faf10a7b24541a64b4541","schema_version":"1.0","event_id":"sha256:369176d5bf8cb7196c33795825a9c1e94cd61d113e9faf10a7b24541a64b4541"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:57GFFSIPDHIWUEHFB427MKWXZK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural Extended Kalman Filters for Learning and Predicting Dynamics of Structural Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CE","nlin.CD","stat.ML"],"primary_cat":"cs.LG","authors_text":"Eleni Chatzi, Kiran Bacsa, Wei Liu, Zhilu Lai","submitted_at":"2022-10-09T04:39:15Z","abstract_excerpt":"Accurate structural response prediction forms a main driver for structural health monitoring and control applications. This often requires the proposed model to adequately capture the underlying dynamics of complex structural systems. In this work, we utilize a learnable Extended Kalman Filter (EKF), named the Neural Extended Kalman Filter (Neural EKF) throughout this paper, for learning the latent evolution dynamics of complex physical systems. The Neural EKF is a generalized version of the conventional EKF, where the modeling of process dynamics and sensory observations can be parameterized "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.04165","kind":"arxiv","version":2},"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/2210.04165/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":"2026-07-05T06:26:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RF7Pjlxpo+heON4JNKd9MfL65Z5zlo6zrrZbkkpGAWIh8YVNAA3f0XNFdWf2jWlTpgr23MHCE7HC4Qa+B5CNAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T18:36:56.073003Z"},"content_sha256":"832c4ec423862d8929ff2481af2e3a2de4df6b690bf2d044bfd60d89b672d099","schema_version":"1.0","event_id":"sha256:832c4ec423862d8929ff2481af2e3a2de4df6b690bf2d044bfd60d89b672d099"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/57GFFSIPDHIWUEHFB427MKWXZK/bundle.json","state_url":"https://pith.science/pith/57GFFSIPDHIWUEHFB427MKWXZK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/57GFFSIPDHIWUEHFB427MKWXZK/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":"2026-08-23T18:36:56Z","links":{"resolver":"https://pith.science/pith/57GFFSIPDHIWUEHFB427MKWXZK","bundle":"https://pith.science/pith/57GFFSIPDHIWUEHFB427MKWXZK/bundle.json","state":"https://pith.science/pith/57GFFSIPDHIWUEHFB427MKWXZK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/57GFFSIPDHIWUEHFB427MKWXZK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:57GFFSIPDHIWUEHFB427MKWXZK","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":"2156c3354b912418b69a7e1a7cfaeae44a6a4b51c4f26e0267838e8ccf2ca40c","cross_cats_sorted":["cs.CE","nlin.CD","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-09T04:39:15Z","title_canon_sha256":"e7d4c9985f6b5a471a561e4dacfbdc6eb6b1a92e57350db5c5439a8c5be56cca"},"schema_version":"1.0","source":{"id":"2210.04165","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.04165","created_at":"2026-07-05T06:26:42Z"},{"alias_kind":"arxiv_version","alias_value":"2210.04165v2","created_at":"2026-07-05T06:26:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.04165","created_at":"2026-07-05T06:26:42Z"},{"alias_kind":"pith_short_12","alias_value":"57GFFSIPDHIW","created_at":"2026-07-05T06:26:42Z"},{"alias_kind":"pith_short_16","alias_value":"57GFFSIPDHIWUEHF","created_at":"2026-07-05T06:26:42Z"},{"alias_kind":"pith_short_8","alias_value":"57GFFSIP","created_at":"2026-07-05T06:26:42Z"}],"graph_snapshots":[{"event_id":"sha256:832c4ec423862d8929ff2481af2e3a2de4df6b690bf2d044bfd60d89b672d099","target":"graph","created_at":"2026-07-05T06:26:42Z","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/2210.04165/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate structural response prediction forms a main driver for structural health monitoring and control applications. This often requires the proposed model to adequately capture the underlying dynamics of complex structural systems. In this work, we utilize a learnable Extended Kalman Filter (EKF), named the Neural Extended Kalman Filter (Neural EKF) throughout this paper, for learning the latent evolution dynamics of complex physical systems. The Neural EKF is a generalized version of the conventional EKF, where the modeling of process dynamics and sensory observations can be parameterized ","authors_text":"Eleni Chatzi, Kiran Bacsa, Wei Liu, Zhilu Lai","cross_cats":["cs.CE","nlin.CD","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-09T04:39:15Z","title":"Neural Extended Kalman Filters for Learning and Predicting Dynamics of Structural Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.04165","kind":"arxiv","version":2},"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":"sha256:369176d5bf8cb7196c33795825a9c1e94cd61d113e9faf10a7b24541a64b4541","target":"record","created_at":"2026-07-05T06:26:42Z","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":"2156c3354b912418b69a7e1a7cfaeae44a6a4b51c4f26e0267838e8ccf2ca40c","cross_cats_sorted":["cs.CE","nlin.CD","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-09T04:39:15Z","title_canon_sha256":"e7d4c9985f6b5a471a561e4dacfbdc6eb6b1a92e57350db5c5439a8c5be56cca"},"schema_version":"1.0","source":{"id":"2210.04165","kind":"arxiv","version":2}},"canonical_sha256":"efcc52c90f19d16a10e50f35f62ad7caa98bf762f0e35efcdd359d4241a3f645","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"efcc52c90f19d16a10e50f35f62ad7caa98bf762f0e35efcdd359d4241a3f645","first_computed_at":"2026-07-05T06:26:42.951716Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:26:42.951716Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XY7iHW+JiZnbNH3iu9Cbf8k5inrcwg/YQlj9jbvJJx5nWT2771xh3xjDKgQsSk2sy3lBtIlIFYywonuATM/eBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:26:42.952210Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.04165","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:369176d5bf8cb7196c33795825a9c1e94cd61d113e9faf10a7b24541a64b4541","sha256:832c4ec423862d8929ff2481af2e3a2de4df6b690bf2d044bfd60d89b672d099"],"state_sha256":"ba6750b720727c9dd085ff0c4cb639273ffc9f33dec75d0d5fa5dcc016ef16a5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DlUGsXXvThjZq5OGRYKiJlEzMPd64zpcf9U42sXqCw1zhdvNB4veoLjPVoKNm6uyjb0ACovJEX+toFjGHENgDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T18:36:56.078776Z","bundle_sha256":"8ed5b3eb179013a6c6e5a472873bfe55f1526e1529f7f8d63483210492fa32ed"}}