{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:66GFKIAV77AQBGL27XSPMLH6IT","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":"d92a0a12207da46fe313f866962b3aee8bacb3dcefec2c9118a3d5b414fcbbda","cross_cats_sorted":["math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-02-23T23:03:56Z","title_canon_sha256":"7076465750cd6cf41b1a22ca2d52f8c68d7a1d740ac7fe7b069f17177550502d"},"schema_version":"1.0","source":{"id":"1602.07349","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.07349","created_at":"2026-05-18T00:50:29Z"},{"alias_kind":"arxiv_version","alias_value":"1602.07349v3","created_at":"2026-05-18T00:50:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.07349","created_at":"2026-05-18T00:50:29Z"},{"alias_kind":"pith_short_12","alias_value":"66GFKIAV77AQ","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_16","alias_value":"66GFKIAV77AQBGL2","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_8","alias_value":"66GFKIAV","created_at":"2026-05-18T12:30:01Z"}],"graph_snapshots":[{"event_id":"sha256:bc0615f77287bbf11ed172b6badee2497f5102ced2650179002ce5a15eac7ff7","target":"graph","created_at":"2026-05-18T00:50:29Z","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 introduce a methodology to construct parsimonious probabilistic models. This method makes use of Information Filtering Networks to produce a robust estimate of the global sparse inverse covariance from a simple sum of local inverse covariances computed on small sub-parts of the network. Being based on local and low-dimensional inversions, this method is computationally very efficient and statistically robust even for the estimation of inverse covariance of high-dimensional, noisy and short time-series. Applied to financial data our method results computationally more efficient than state-of","authors_text":"Guido Previde Massara, T. Di Matteo, Tomaso Aste, Wolfram Barfuss","cross_cats":["math.IT","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-02-23T23:03:56Z","title":"Parsimonious modeling with Information Filtering Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.07349","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:e88e8dec9aef59e6ebfd4b43abd2d0367611256771c3b66b05297870c3d7e775","target":"record","created_at":"2026-05-18T00:50:29Z","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":"d92a0a12207da46fe313f866962b3aee8bacb3dcefec2c9118a3d5b414fcbbda","cross_cats_sorted":["math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-02-23T23:03:56Z","title_canon_sha256":"7076465750cd6cf41b1a22ca2d52f8c68d7a1d740ac7fe7b069f17177550502d"},"schema_version":"1.0","source":{"id":"1602.07349","kind":"arxiv","version":3}},"canonical_sha256":"f78c552015ffc100997afde4f62cfe44fecf37e3b55fde7082a28b59b32eae0a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f78c552015ffc100997afde4f62cfe44fecf37e3b55fde7082a28b59b32eae0a","first_computed_at":"2026-05-18T00:50:29.698545Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:50:29.698545Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"X82RttonRlauSE30Eu6c2LU5m6O1VVsVCZY7/VCqn62q4i9cbAP/Cdikfqza3jSLL4vS/jREatXj/hX8STcvBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:50:29.699329Z","signed_message":"canonical_sha256_bytes"},"source_id":"1602.07349","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e88e8dec9aef59e6ebfd4b43abd2d0367611256771c3b66b05297870c3d7e775","sha256:bc0615f77287bbf11ed172b6badee2497f5102ced2650179002ce5a15eac7ff7"],"state_sha256":"360b8f2ef7488c4e74f5979cb6ceb1fd4803b55daaec34b3efe1e95b9a83d633"}