{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:K32LN5RIBO7T5XXD5EQURM4PHN","short_pith_number":"pith:K32LN5RI","canonical_record":{"source":{"id":"2210.02166","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2022-10-05T11:48:48Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"2d00221ed571ef10402d741a348e59f97d32b7268e829d2fee7a49969bbc6f30","abstract_canon_sha256":"95b05aaeddfadefc74c63bf51e81afea58b3dc061f9d7f065a622029cb546a0a"},"schema_version":"1.0"},"canonical_sha256":"56f4b6f6280bbf3edee3e92148b38f3b49ab1a692a3650af0961f63b0ac555be","source":{"kind":"arxiv","id":"2210.02166","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.02166","created_at":"2026-07-05T06:56:30Z"},{"alias_kind":"arxiv_version","alias_value":"2210.02166v4","created_at":"2026-07-05T06:56:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.02166","created_at":"2026-07-05T06:56:30Z"},{"alias_kind":"pith_short_12","alias_value":"K32LN5RIBO7T","created_at":"2026-07-05T06:56:30Z"},{"alias_kind":"pith_short_16","alias_value":"K32LN5RIBO7T5XXD","created_at":"2026-07-05T06:56:30Z"},{"alias_kind":"pith_short_8","alias_value":"K32LN5RI","created_at":"2026-07-05T06:56:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:K32LN5RIBO7T5XXD5EQURM4PHN","target":"record","payload":{"canonical_record":{"source":{"id":"2210.02166","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2022-10-05T11:48:48Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"2d00221ed571ef10402d741a348e59f97d32b7268e829d2fee7a49969bbc6f30","abstract_canon_sha256":"95b05aaeddfadefc74c63bf51e81afea58b3dc061f9d7f065a622029cb546a0a"},"schema_version":"1.0"},"canonical_sha256":"56f4b6f6280bbf3edee3e92148b38f3b49ab1a692a3650af0961f63b0ac555be","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:56:30.085103Z","signature_b64":"UHHqMquR4cm3kkRQYVQkFSCI4CeTlOcUumlE+0hAev9gGf5MVzR5WlOJfM2zm0l1ZwBmT/VU8Q7Sn4EvcThqDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"56f4b6f6280bbf3edee3e92148b38f3b49ab1a692a3650af0961f63b0ac555be","last_reissued_at":"2026-07-05T06:56:30.084632Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:56:30.084632Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.02166","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:56:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oEz5u0BxasvQhVYslb2AaYbni2qf5e1Hv+iWJ11KuQC7fjTYtpXgFxdIFwpa3mJMfrEWwo2hesoySsA/GEdgAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T17:07:05.203236Z"},"content_sha256":"f1235f10d641254aad54c488c5fe1b9874db6feb35cf8b1de13ba7e73b21be05","schema_version":"1.0","event_id":"sha256:f1235f10d641254aad54c488c5fe1b9874db6feb35cf8b1de13ba7e73b21be05"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:K32LN5RIBO7T5XXD5EQURM4PHN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Robust Bayesian Inference for Moving Horizon Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Angelo Alessandri, Chang Liu, Shengbo Eben Li, Wei Pan, Wenhan Cao, Zhiqian Lan","submitted_at":"2022-10-05T11:48:48Z","abstract_excerpt":"The accuracy of moving horizon estimation (MHE) suffers significantly in the presence of measurement outliers. Existing methods address this issue by treating measurements leading to large MHE cost function values as outliers, which are subsequently discarded. This strategy, achieved through solving combinatorial optimization problems, is confined to linear systems to guarantee computational tractability and stability. Contrasting these heuristic solutions, our work reexamines MHE from a Bayesian perspective, unveils the fundamental issue of its lack of robustness: MHE's sensitivity to outlier"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.02166","kind":"arxiv","version":4},"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/2210.02166/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":"2026-07-05T06:56:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lM5Rg5Ln6DCTi3blB3v8PNILlKUNO7vOmf/YhLVHBio4r+dPBR9oKTk45prkWvCddh0UiANBaQ7sqF75/eRcAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T17:07:05.203598Z"},"content_sha256":"f0fff8ab2b21a2bd6edb588e59c82317b8a16ba7f0649cbb7f26603783d9f4cc","schema_version":"1.0","event_id":"sha256:f0fff8ab2b21a2bd6edb588e59c82317b8a16ba7f0649cbb7f26603783d9f4cc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/K32LN5RIBO7T5XXD5EQURM4PHN/bundle.json","state_url":"https://pith.science/pith/K32LN5RIBO7T5XXD5EQURM4PHN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/K32LN5RIBO7T5XXD5EQURM4PHN/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":"2026-08-21T17:07:05Z","links":{"resolver":"https://pith.science/pith/K32LN5RIBO7T5XXD5EQURM4PHN","bundle":"https://pith.science/pith/K32LN5RIBO7T5XXD5EQURM4PHN/bundle.json","state":"https://pith.science/pith/K32LN5RIBO7T5XXD5EQURM4PHN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/K32LN5RIBO7T5XXD5EQURM4PHN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:K32LN5RIBO7T5XXD5EQURM4PHN","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":"95b05aaeddfadefc74c63bf51e81afea58b3dc061f9d7f065a622029cb546a0a","cross_cats_sorted":["cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2022-10-05T11:48:48Z","title_canon_sha256":"2d00221ed571ef10402d741a348e59f97d32b7268e829d2fee7a49969bbc6f30"},"schema_version":"1.0","source":{"id":"2210.02166","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.02166","created_at":"2026-07-05T06:56:30Z"},{"alias_kind":"arxiv_version","alias_value":"2210.02166v4","created_at":"2026-07-05T06:56:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.02166","created_at":"2026-07-05T06:56:30Z"},{"alias_kind":"pith_short_12","alias_value":"K32LN5RIBO7T","created_at":"2026-07-05T06:56:30Z"},{"alias_kind":"pith_short_16","alias_value":"K32LN5RIBO7T5XXD","created_at":"2026-07-05T06:56:30Z"},{"alias_kind":"pith_short_8","alias_value":"K32LN5RI","created_at":"2026-07-05T06:56:30Z"}],"graph_snapshots":[{"event_id":"sha256:f0fff8ab2b21a2bd6edb588e59c82317b8a16ba7f0649cbb7f26603783d9f4cc","target":"graph","created_at":"2026-07-05T06:56:30Z","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/2210.02166/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The accuracy of moving horizon estimation (MHE) suffers significantly in the presence of measurement outliers. Existing methods address this issue by treating measurements leading to large MHE cost function values as outliers, which are subsequently discarded. This strategy, achieved through solving combinatorial optimization problems, is confined to linear systems to guarantee computational tractability and stability. Contrasting these heuristic solutions, our work reexamines MHE from a Bayesian perspective, unveils the fundamental issue of its lack of robustness: MHE's sensitivity to outlier","authors_text":"Angelo Alessandri, Chang Liu, Shengbo Eben Li, Wei Pan, Wenhan Cao, Zhiqian Lan","cross_cats":["cs.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2022-10-05T11:48:48Z","title":"Robust Bayesian Inference for Moving Horizon Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.02166","kind":"arxiv","version":4},"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:f1235f10d641254aad54c488c5fe1b9874db6feb35cf8b1de13ba7e73b21be05","target":"record","created_at":"2026-07-05T06:56:30Z","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":"95b05aaeddfadefc74c63bf51e81afea58b3dc061f9d7f065a622029cb546a0a","cross_cats_sorted":["cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2022-10-05T11:48:48Z","title_canon_sha256":"2d00221ed571ef10402d741a348e59f97d32b7268e829d2fee7a49969bbc6f30"},"schema_version":"1.0","source":{"id":"2210.02166","kind":"arxiv","version":4}},"canonical_sha256":"56f4b6f6280bbf3edee3e92148b38f3b49ab1a692a3650af0961f63b0ac555be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"56f4b6f6280bbf3edee3e92148b38f3b49ab1a692a3650af0961f63b0ac555be","first_computed_at":"2026-07-05T06:56:30.084632Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:56:30.084632Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UHHqMquR4cm3kkRQYVQkFSCI4CeTlOcUumlE+0hAev9gGf5MVzR5WlOJfM2zm0l1ZwBmT/VU8Q7Sn4EvcThqDw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:56:30.085103Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.02166","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f1235f10d641254aad54c488c5fe1b9874db6feb35cf8b1de13ba7e73b21be05","sha256:f0fff8ab2b21a2bd6edb588e59c82317b8a16ba7f0649cbb7f26603783d9f4cc"],"state_sha256":"b57200b5b3caea92dd24259ab9c95b31024e431ce401746666f65922397d3632"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tUq3wRf0E2uB43T2dgMSHBNaiD8En0hFzb4ebmvqV2H68FTQZX4WLYGY7wAi5/XNJCkqAaHwrKpy1ZSqsFP8Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T17:07:05.207307Z","bundle_sha256":"1c55472464ea45cb8d273016f16dad5d0e54a87b17f8993cb9e6765aa2f7c74f"}}