{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:UFNMLIGRYR6XTUO5AO4UDYNXFJ","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":"cac95b25c0ca65b6fa82025e58e13d3df60788d16f7309c7f41051484bcbc58b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-29T06:51:58Z","title_canon_sha256":"517d1093f87584dacb5d362ed2fcba5dff5e53953159c660064e531402f60969"},"schema_version":"1.0","source":{"id":"2507.21531","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.21531","created_at":"2026-07-05T11:45:01Z"},{"alias_kind":"arxiv_version","alias_value":"2507.21531v1","created_at":"2026-07-05T11:45:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.21531","created_at":"2026-07-05T11:45:01Z"},{"alias_kind":"pith_short_12","alias_value":"UFNMLIGRYR6X","created_at":"2026-07-05T11:45:01Z"},{"alias_kind":"pith_short_16","alias_value":"UFNMLIGRYR6XTUO5","created_at":"2026-07-05T11:45:01Z"},{"alias_kind":"pith_short_8","alias_value":"UFNMLIGR","created_at":"2026-07-05T11:45:01Z"}],"graph_snapshots":[{"event_id":"sha256:81fa6f4677660e8e3e22bb0c8475a73aec414b01d54a6a4328367449519e1d34","target":"graph","created_at":"2026-07-05T11:45:01Z","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/2507.21531/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The manifold hypothesis suggests that high-dimensional neural time series lie on a low-dimensional manifold shaped by simpler underlying dynamics. To uncover this structure, latent dynamical variable models such as state-space models, recurrent neural networks, neural ordinary differential equations, and Gaussian Process Latent Variable Models are widely used. We propose a novel hierarchical stochastic differential equation (SDE) model that balances computational efficiency and interpretability, addressing key limitations of existing methods. Our model assumes the trajectory of a manifold can ","authors_text":"Ali Yousefi, Behzad Nazari, Maryam Ostadsharif Memar, Navid Ziaei, Pedram Rajaei","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-29T06:51:58Z","title":"Hierarchical Stochastic Differential Equation Models for Latent Manifold Learning in Neural Time Series"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.21531","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":"sha256:78509e10bd7baa0ba52fe8919f43a9e228d79ea0cc2c0d3462bcbfc3d73e3ab5","target":"record","created_at":"2026-07-05T11:45:01Z","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":"cac95b25c0ca65b6fa82025e58e13d3df60788d16f7309c7f41051484bcbc58b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-29T06:51:58Z","title_canon_sha256":"517d1093f87584dacb5d362ed2fcba5dff5e53953159c660064e531402f60969"},"schema_version":"1.0","source":{"id":"2507.21531","kind":"arxiv","version":1}},"canonical_sha256":"a15ac5a0d1c47d79d1dd03b941e1b72a56c509ae89e91d5a5fed611afb5d0912","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a15ac5a0d1c47d79d1dd03b941e1b72a56c509ae89e91d5a5fed611afb5d0912","first_computed_at":"2026-07-05T11:45:01.851139Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:45:01.851139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jXqIBw8CG+cuMgZ1++mfSRWB2bvjK6Ed/zn/zendL/wcT3hoog4h7I2rOWGtN6QKa6HtPtjfZM2VCSA/rPcRDw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:45:01.851536Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.21531","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:78509e10bd7baa0ba52fe8919f43a9e228d79ea0cc2c0d3462bcbfc3d73e3ab5","sha256:81fa6f4677660e8e3e22bb0c8475a73aec414b01d54a6a4328367449519e1d34"],"state_sha256":"c0bfb5f9aa8fc60e7e336e82f17731287084ce4b829e125cfe57c34c6d2d85b2"}