{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:JUX5IRER5LEDI6PEBUSDUZUYTG","short_pith_number":"pith:JUX5IRER","schema_version":"1.0","canonical_sha256":"4d2fd44491eac83479e40d243a669899aeb9862024653499e9126cc6b67eef66","source":{"kind":"arxiv","id":"2411.15637","version":3},"attestation_state":"computed","paper":{"title":"GraphGrad: Efficient Estimation of Sparse Polynomial Representations for General State-Space Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"Benjamin Cox, Emilie Chouzenoux, Victor Elvira","submitted_at":"2024-11-23T19:27:49Z","abstract_excerpt":"State-space models (SSMs) are a powerful statistical tool for modelling time-varying systems via a latent state. In these models, the latent state is never directly observed. Instead, a sequence of observations related to the state is available. The state-space model is defined by the state dynamics and the observation model, both of which are described by parametric distributions. Estimation of parameters of these distributions is a very challenging, but essential, task for performing inference and prediction. Furthermore, it is typical that not all states of the system interact. We can there"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2411.15637","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2024-11-23T19:27:49Z","cross_cats_sorted":[],"title_canon_sha256":"36e4e9e6007465c36e159a0c83f8daec36a1bd77eb196204c57d18d28d529993","abstract_canon_sha256":"09109c3ddb6b7ae70d61a1df49323ed533f4bbb367b26f3eab7fbf2a5a2b30d7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:37:38.344163Z","signature_b64":"IJGqlisuYzchDdSzNUXX2uBFtevyJ+uU3B2HrklietzKCaKjL+z9azLbYwVcvOql3pY93fNWq0RDnBNP3AA5BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4d2fd44491eac83479e40d243a669899aeb9862024653499e9126cc6b67eef66","last_reissued_at":"2026-07-05T10:37:38.343153Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:37:38.343153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GraphGrad: Efficient Estimation of Sparse Polynomial Representations for General State-Space Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"Benjamin Cox, Emilie Chouzenoux, Victor Elvira","submitted_at":"2024-11-23T19:27:49Z","abstract_excerpt":"State-space models (SSMs) are a powerful statistical tool for modelling time-varying systems via a latent state. In these models, the latent state is never directly observed. Instead, a sequence of observations related to the state is available. The state-space model is defined by the state dynamics and the observation model, both of which are described by parametric distributions. Estimation of parameters of these distributions is a very challenging, but essential, task for performing inference and prediction. Furthermore, it is typical that not all states of the system interact. We can there"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.15637","kind":"arxiv","version":3},"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/2411.15637/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2411.15637","created_at":"2026-07-05T10:37:38.343289+00:00"},{"alias_kind":"arxiv_version","alias_value":"2411.15637v3","created_at":"2026-07-05T10:37:38.343289+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.15637","created_at":"2026-07-05T10:37:38.343289+00:00"},{"alias_kind":"pith_short_12","alias_value":"JUX5IRER5LED","created_at":"2026-07-05T10:37:38.343289+00:00"},{"alias_kind":"pith_short_16","alias_value":"JUX5IRER5LEDI6PE","created_at":"2026-07-05T10:37:38.343289+00:00"},{"alias_kind":"pith_short_8","alias_value":"JUX5IRER","created_at":"2026-07-05T10:37:38.343289+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/JUX5IRER5LEDI6PEBUSDUZUYTG","json":"https://pith.science/pith/JUX5IRER5LEDI6PEBUSDUZUYTG.json","graph_json":"https://pith.science/api/pith-number/JUX5IRER5LEDI6PEBUSDUZUYTG/graph.json","events_json":"https://pith.science/api/pith-number/JUX5IRER5LEDI6PEBUSDUZUYTG/events.json","paper":"https://pith.science/paper/JUX5IRER"},"agent_actions":{"view_html":"https://pith.science/pith/JUX5IRER5LEDI6PEBUSDUZUYTG","download_json":"https://pith.science/pith/JUX5IRER5LEDI6PEBUSDUZUYTG.json","view_paper":"https://pith.science/paper/JUX5IRER","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2411.15637&json=true","fetch_graph":"https://pith.science/api/pith-number/JUX5IRER5LEDI6PEBUSDUZUYTG/graph.json","fetch_events":"https://pith.science/api/pith-number/JUX5IRER5LEDI6PEBUSDUZUYTG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JUX5IRER5LEDI6PEBUSDUZUYTG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JUX5IRER5LEDI6PEBUSDUZUYTG/action/storage_attestation","attest_author":"https://pith.science/pith/JUX5IRER5LEDI6PEBUSDUZUYTG/action/author_attestation","sign_citation":"https://pith.science/pith/JUX5IRER5LEDI6PEBUSDUZUYTG/action/citation_signature","submit_replication":"https://pith.science/pith/JUX5IRER5LEDI6PEBUSDUZUYTG/action/replication_record"}},"created_at":"2026-07-05T10:37:38.343289+00:00","updated_at":"2026-07-05T10:37:38.343289+00:00"}