{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:5K2VLABP6ZDJHAZ34B3LYBCV5C","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":"1cf7992d9b028b532c1a357119e83041300ced302c12cc320dcd5a22e37c4bfb","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-08-19T15:29:43Z","title_canon_sha256":"230b460b6a7b09e6738ecf284fccd3c359b5b183d4fb2c9724efa5233d79ba42"},"schema_version":"1.0","source":{"id":"2208.09399","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.09399","created_at":"2026-07-05T06:07:32Z"},{"alias_kind":"arxiv_version","alias_value":"2208.09399v3","created_at":"2026-07-05T06:07:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.09399","created_at":"2026-07-05T06:07:32Z"},{"alias_kind":"pith_short_12","alias_value":"5K2VLABP6ZDJ","created_at":"2026-07-05T06:07:32Z"},{"alias_kind":"pith_short_16","alias_value":"5K2VLABP6ZDJHAZ3","created_at":"2026-07-05T06:07:32Z"},{"alias_kind":"pith_short_8","alias_value":"5K2VLABP","created_at":"2026-07-05T06:07:32Z"}],"graph_snapshots":[{"event_id":"sha256:391d12e7459f3ab051564d7db368b4d855e7de1b1061d8d25f20f560cf3cde49","target":"graph","created_at":"2026-07-05T06:07:32Z","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/2208.09399/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The imputation of missing values represents a significant obstacle for many real-world data analysis pipelines. Here, we focus on time series data and put forward SSSD, an imputation model that relies on two emerging technologies, (conditional) diffusion models as state-of-the-art generative models and structured state space models as internal model architecture, which are particularly suited to capture long-term dependencies in time series data. We demonstrate that SSSD matches or even exceeds state-of-the-art probabilistic imputation and forecasting performance on a broad range of data sets ","authors_text":"Juan Miguel Lopez Alcaraz, Nils Strodthoff","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-08-19T15:29:43Z","title":"Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.09399","kind":"arxiv","version":3},"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":"sha256:5461b3f329f8bfb684b915f2369ed2dc5d66d630cea002143afcd243fa86d239","target":"record","created_at":"2026-07-05T06:07:32Z","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":"1cf7992d9b028b532c1a357119e83041300ced302c12cc320dcd5a22e37c4bfb","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-08-19T15:29:43Z","title_canon_sha256":"230b460b6a7b09e6738ecf284fccd3c359b5b183d4fb2c9724efa5233d79ba42"},"schema_version":"1.0","source":{"id":"2208.09399","kind":"arxiv","version":3}},"canonical_sha256":"eab555802ff64693833be076bc0455e8811d58f7c3283ba722889e30c16e769b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eab555802ff64693833be076bc0455e8811d58f7c3283ba722889e30c16e769b","first_computed_at":"2026-07-05T06:07:32.043713Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:07:32.043713Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hUiqlkClgtZ2jkQy/K5gYFAJ38GivtpN7Uueu29GcPyqqb4NqzoOWwxmoGZvSRzMvLtxl+9kmBf4r/mXAgpvDA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:07:32.044139Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.09399","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5461b3f329f8bfb684b915f2369ed2dc5d66d630cea002143afcd243fa86d239","sha256:391d12e7459f3ab051564d7db368b4d855e7de1b1061d8d25f20f560cf3cde49"],"state_sha256":"a5f3d7d88cbdbe0c313b44fec93b0339f6e70019dc09b6acbdcb0f87fd7356d0"}