{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:XYYU3HHNKP5WSXZLL5BCQ2XNWT","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":"90bf19ce93ac4ad6b170dcaf307d6cf5ee152fd6d87ba021cd5e87032bb7ed09","cross_cats_sorted":["cs.LG","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2024-12-04T23:14:00Z","title_canon_sha256":"354321b6d3bc4c620802441c0c005749776ce7c0143602aebdaafa644f9a1a17"},"schema_version":"1.0","source":{"id":"2412.03768","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.03768","created_at":"2026-07-05T11:28:12Z"},{"alias_kind":"arxiv_version","alias_value":"2412.03768v2","created_at":"2026-07-05T11:28:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.03768","created_at":"2026-07-05T11:28:12Z"},{"alias_kind":"pith_short_12","alias_value":"XYYU3HHNKP5W","created_at":"2026-07-05T11:28:12Z"},{"alias_kind":"pith_short_16","alias_value":"XYYU3HHNKP5WSXZL","created_at":"2026-07-05T11:28:12Z"},{"alias_kind":"pith_short_8","alias_value":"XYYU3HHN","created_at":"2026-07-05T11:28:12Z"}],"graph_snapshots":[{"event_id":"sha256:dbff069afec6d2cc6efe491de1d4fef8711791c31bf0c22410888cbc9a80c5c5","target":"graph","created_at":"2026-07-05T11:28:12Z","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/2412.03768/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Complex networked systems driven by latent inputs are common in fields like neuroscience, finance, and engineering. A key inference problem here is to learn edge connectivity from node outputs (potentials). We focus on systems governed by steady-state linear conservation laws: $X_t = {L^{\\ast}}Y_{t}$, where $X_t, Y_t \\in \\mathbb{R}^p$ denote inputs and potentials, respectively, and the sparsity pattern of the $p \\times p$ Laplacian $L^{\\ast}$ encodes the edge structure. Assuming $X_t$ to be a wide-sense stationary stochastic process with a known spectral density matrix, we learn the support of","authors_text":"Anirudh Rayas, Deepjyoti Deka, Gautam Dasarathy, Jiajun Cheng, Rajasekhar Anguluri","cross_cats":["cs.LG","eess.SP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2024-12-04T23:14:00Z","title":"Learning Networks from Wide-Sense Stationary Stochastic Processes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.03768","kind":"arxiv","version":2},"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":"sha256:95f6c5e5168d19ac51f73d632958788c811a325d7c0398701a4b9a66ccdf8b66","target":"record","created_at":"2026-07-05T11:28:12Z","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":"90bf19ce93ac4ad6b170dcaf307d6cf5ee152fd6d87ba021cd5e87032bb7ed09","cross_cats_sorted":["cs.LG","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2024-12-04T23:14:00Z","title_canon_sha256":"354321b6d3bc4c620802441c0c005749776ce7c0143602aebdaafa644f9a1a17"},"schema_version":"1.0","source":{"id":"2412.03768","kind":"arxiv","version":2}},"canonical_sha256":"be314d9ced53fb695f2b5f42286aedb4e8b88b98aae3697e1cf8962d962437f1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"be314d9ced53fb695f2b5f42286aedb4e8b88b98aae3697e1cf8962d962437f1","first_computed_at":"2026-07-05T11:28:12.666014Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:28:12.666014Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vk+SiHKtJzhQfBMgeuyPR3uuCsuuVHCn458xIXSSWnnvNwWFQGIgmCOtK/3sYLLX/EtP9UsS7lsVxfiJb9j6Bg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:28:12.666616Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.03768","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:95f6c5e5168d19ac51f73d632958788c811a325d7c0398701a4b9a66ccdf8b66","sha256:dbff069afec6d2cc6efe491de1d4fef8711791c31bf0c22410888cbc9a80c5c5"],"state_sha256":"da8368cae3a67a4b7a14be442776b5b0ea06765c1298503a809f0a1c8ba91299"}