{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:25RUJ2PPCY4USVVI4HPHLT2BVG","short_pith_number":"pith:25RUJ2PP","canonical_record":{"source":{"id":"1203.4345","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2012-03-20T08:51:50Z","cross_cats_sorted":["cs.AI","cs.RO","stat.ML"],"title_canon_sha256":"8bd211c4a3938c00accebc15e94ec75556f698da8022d155e784948df9069858","abstract_canon_sha256":"09fd72e9bc26099ca8f7b0f54f47d825b454ce4fed3dfff4cc127b10045afbfb"},"schema_version":"1.0"},"canonical_sha256":"d76344e9ef16394956a8e1de75cf41a9a2524751d369fb79c7fac40706fc18d8","source":{"kind":"arxiv","id":"1203.4345","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1203.4345","created_at":"2026-05-18T03:49:00Z"},{"alias_kind":"arxiv_version","alias_value":"1203.4345v1","created_at":"2026-05-18T03:49:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1203.4345","created_at":"2026-05-18T03:49:00Z"},{"alias_kind":"pith_short_12","alias_value":"25RUJ2PPCY4U","created_at":"2026-05-18T12:26:50Z"},{"alias_kind":"pith_short_16","alias_value":"25RUJ2PPCY4USVVI","created_at":"2026-05-18T12:26:50Z"},{"alias_kind":"pith_short_8","alias_value":"25RUJ2PP","created_at":"2026-05-18T12:26:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:25RUJ2PPCY4USVVI4HPHLT2BVG","target":"record","payload":{"canonical_record":{"source":{"id":"1203.4345","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2012-03-20T08:51:50Z","cross_cats_sorted":["cs.AI","cs.RO","stat.ML"],"title_canon_sha256":"8bd211c4a3938c00accebc15e94ec75556f698da8022d155e784948df9069858","abstract_canon_sha256":"09fd72e9bc26099ca8f7b0f54f47d825b454ce4fed3dfff4cc127b10045afbfb"},"schema_version":"1.0"},"canonical_sha256":"d76344e9ef16394956a8e1de75cf41a9a2524751d369fb79c7fac40706fc18d8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:49:00.907394Z","signature_b64":"kPkO47AqH/iopdH7+0RaixGpL7a/A6NW1S+q4fQ7N43s2IVglBGShqo5JVp3aaWcd4D9qrde6VrdofeqjnvCCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d76344e9ef16394956a8e1de75cf41a9a2524751d369fb79c7fac40706fc18d8","last_reissued_at":"2026-05-18T03:49:00.906901Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:49:00.906901Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1203.4345","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":"2026-05-18T03:49:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XhEHXLmFt+xBsQNpNBqKWt4gJ/DZg4zmHxpP3luElpSSIWugSzNIc5Z9Jek28MasoA0QVQBv0lvvA1YgsDn7AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T10:20:58.886992Z"},"content_sha256":"cd94d4f35e6e596f371a627754560ec049e2b74a2b661061765cb73a061b1225","schema_version":"1.0","event_id":"sha256:cd94d4f35e6e596f371a627754560ec049e2b74a2b661061765cb73a061b1225"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:25RUJ2PPCY4USVVI4HPHLT2BVG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Robust Filtering and Smoothing with Gaussian Processes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.RO","stat.ML"],"primary_cat":"cs.SY","authors_text":"Carl Edward Rasmussen, Marco F. Huber, Marc Peter Deisenroth, Ryan Turner, Uwe D. Hanebeck","submitted_at":"2012-03-20T08:51:50Z","abstract_excerpt":"We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP) models. GPs are gaining increasing importance in signal processing, machine learning, robotics, and control for representing unknown system functions by posterior probability distributions. This modern way of \"system identification\" is more robust than finding point estimates of a parametric function representation. In this article, we present a principled algori"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1203.4345","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":""},"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":"2026-05-18T03:49:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4ZUwdyvvPIdrZnw/37kO935v4lUxdWrJ7B7u048E8OyD+ZiwGN5PGya9OD6yMMHyfhoaUWKDVJtujlujUOBTDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T10:20:58.887676Z"},"content_sha256":"c6b32f61fd070004944e93f9a110b0dde0f0f5ddd7502f92a711910c3ae1058e","schema_version":"1.0","event_id":"sha256:c6b32f61fd070004944e93f9a110b0dde0f0f5ddd7502f92a711910c3ae1058e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/25RUJ2PPCY4USVVI4HPHLT2BVG/bundle.json","state_url":"https://pith.science/pith/25RUJ2PPCY4USVVI4HPHLT2BVG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/25RUJ2PPCY4USVVI4HPHLT2BVG/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":"2026-05-25T10:20:58Z","links":{"resolver":"https://pith.science/pith/25RUJ2PPCY4USVVI4HPHLT2BVG","bundle":"https://pith.science/pith/25RUJ2PPCY4USVVI4HPHLT2BVG/bundle.json","state":"https://pith.science/pith/25RUJ2PPCY4USVVI4HPHLT2BVG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/25RUJ2PPCY4USVVI4HPHLT2BVG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:25RUJ2PPCY4USVVI4HPHLT2BVG","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":"09fd72e9bc26099ca8f7b0f54f47d825b454ce4fed3dfff4cc127b10045afbfb","cross_cats_sorted":["cs.AI","cs.RO","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2012-03-20T08:51:50Z","title_canon_sha256":"8bd211c4a3938c00accebc15e94ec75556f698da8022d155e784948df9069858"},"schema_version":"1.0","source":{"id":"1203.4345","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1203.4345","created_at":"2026-05-18T03:49:00Z"},{"alias_kind":"arxiv_version","alias_value":"1203.4345v1","created_at":"2026-05-18T03:49:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1203.4345","created_at":"2026-05-18T03:49:00Z"},{"alias_kind":"pith_short_12","alias_value":"25RUJ2PPCY4U","created_at":"2026-05-18T12:26:50Z"},{"alias_kind":"pith_short_16","alias_value":"25RUJ2PPCY4USVVI","created_at":"2026-05-18T12:26:50Z"},{"alias_kind":"pith_short_8","alias_value":"25RUJ2PP","created_at":"2026-05-18T12:26:50Z"}],"graph_snapshots":[{"event_id":"sha256:c6b32f61fd070004944e93f9a110b0dde0f0f5ddd7502f92a711910c3ae1058e","target":"graph","created_at":"2026-05-18T03:49:00Z","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"},"paper":{"abstract_excerpt":"We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP) models. GPs are gaining increasing importance in signal processing, machine learning, robotics, and control for representing unknown system functions by posterior probability distributions. This modern way of \"system identification\" is more robust than finding point estimates of a parametric function representation. In this article, we present a principled algori","authors_text":"Carl Edward Rasmussen, Marco F. Huber, Marc Peter Deisenroth, Ryan Turner, Uwe D. Hanebeck","cross_cats":["cs.AI","cs.RO","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2012-03-20T08:51:50Z","title":"Robust Filtering and Smoothing with Gaussian Processes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1203.4345","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:cd94d4f35e6e596f371a627754560ec049e2b74a2b661061765cb73a061b1225","target":"record","created_at":"2026-05-18T03:49:00Z","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":"09fd72e9bc26099ca8f7b0f54f47d825b454ce4fed3dfff4cc127b10045afbfb","cross_cats_sorted":["cs.AI","cs.RO","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2012-03-20T08:51:50Z","title_canon_sha256":"8bd211c4a3938c00accebc15e94ec75556f698da8022d155e784948df9069858"},"schema_version":"1.0","source":{"id":"1203.4345","kind":"arxiv","version":1}},"canonical_sha256":"d76344e9ef16394956a8e1de75cf41a9a2524751d369fb79c7fac40706fc18d8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d76344e9ef16394956a8e1de75cf41a9a2524751d369fb79c7fac40706fc18d8","first_computed_at":"2026-05-18T03:49:00.906901Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:49:00.906901Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kPkO47AqH/iopdH7+0RaixGpL7a/A6NW1S+q4fQ7N43s2IVglBGShqo5JVp3aaWcd4D9qrde6VrdofeqjnvCCA==","signature_status":"signed_v1","signed_at":"2026-05-18T03:49:00.907394Z","signed_message":"canonical_sha256_bytes"},"source_id":"1203.4345","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cd94d4f35e6e596f371a627754560ec049e2b74a2b661061765cb73a061b1225","sha256:c6b32f61fd070004944e93f9a110b0dde0f0f5ddd7502f92a711910c3ae1058e"],"state_sha256":"4d86bfe8b68f4e91edb2835cb0f41852c5192f90ba03ed61f37d27fca36afb7e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PVBXMTPvut3pH8WmHuPtqln6Yghu8bSogPyByDT2tLzTE0UEqhlp9D98XmHCJxbi4qQqwAAw+oTkMpodhoHGCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T10:20:58.891112Z","bundle_sha256":"16470ef790642f26c06d9140cdd746b236c21f28b37ee846c2c9bd471cff9dd3"}}