{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:JYBPAWINIB7VEIUT6GQWZE7TV2","short_pith_number":"pith:JYBPAWIN","schema_version":"1.0","canonical_sha256":"4e02f0590d407f522293f1a16c93f3aeb0c0fa894d3a6e112d77f644798b5e81","source":{"kind":"arxiv","id":"1505.05668","version":3},"attestation_state":"computed","paper":{"title":"Locally Adaptive Dynamic Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"stat.AP","authors_text":"Daniele Durante, David B. Dunson","submitted_at":"2015-05-21T10:27:53Z","abstract_excerpt":"Our focus is on realistically modeling and forecasting dynamic networks of face-to-face contacts among individuals. Important aspects of such data that lead to problems with current methods include the tendency of the contacts to move between periods of slow and rapid changes, and the dynamic heterogeneity in the actors' connectivity behaviors. Motivated by this application, we develop a novel method for Locally Adaptive DYnamic (LADY) network inference. The proposed model relies on a dynamic latent space representation in which each actor's position evolves in time via stochastic differential"},"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":"1505.05668","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2015-05-21T10:27:53Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"3fa3978dbca584a21f13a85a9cdb073ac10c09840d835392cb06d3138d2e1787","abstract_canon_sha256":"ee7ede9da170d3bc409da580930aaf0eb8a58b61a790f0e8c26ad9114714bfb5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:06:12.795716Z","signature_b64":"f4Mk840p8woCsJkIKtR7XJHOiU3fG2boyHa/35x0lw4jwmRk8LMyY/nef74M0cXbyNNFiZm2BmTebvRFbYbYAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4e02f0590d407f522293f1a16c93f3aeb0c0fa894d3a6e112d77f644798b5e81","last_reissued_at":"2026-05-18T00:06:12.794979Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:06:12.794979Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Locally Adaptive Dynamic Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"stat.AP","authors_text":"Daniele Durante, David B. Dunson","submitted_at":"2015-05-21T10:27:53Z","abstract_excerpt":"Our focus is on realistically modeling and forecasting dynamic networks of face-to-face contacts among individuals. Important aspects of such data that lead to problems with current methods include the tendency of the contacts to move between periods of slow and rapid changes, and the dynamic heterogeneity in the actors' connectivity behaviors. Motivated by this application, we develop a novel method for Locally Adaptive DYnamic (LADY) network inference. The proposed model relies on a dynamic latent space representation in which each actor's position evolves in time via stochastic differential"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1505.05668","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":""},"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":"1505.05668","created_at":"2026-05-18T00:06:12.795099+00:00"},{"alias_kind":"arxiv_version","alias_value":"1505.05668v3","created_at":"2026-05-18T00:06:12.795099+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1505.05668","created_at":"2026-05-18T00:06:12.795099+00:00"},{"alias_kind":"pith_short_12","alias_value":"JYBPAWINIB7V","created_at":"2026-05-18T12:29:27.538025+00:00"},{"alias_kind":"pith_short_16","alias_value":"JYBPAWINIB7VEIUT","created_at":"2026-05-18T12:29:27.538025+00:00"},{"alias_kind":"pith_short_8","alias_value":"JYBPAWIN","created_at":"2026-05-18T12:29:27.538025+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/JYBPAWINIB7VEIUT6GQWZE7TV2","json":"https://pith.science/pith/JYBPAWINIB7VEIUT6GQWZE7TV2.json","graph_json":"https://pith.science/api/pith-number/JYBPAWINIB7VEIUT6GQWZE7TV2/graph.json","events_json":"https://pith.science/api/pith-number/JYBPAWINIB7VEIUT6GQWZE7TV2/events.json","paper":"https://pith.science/paper/JYBPAWIN"},"agent_actions":{"view_html":"https://pith.science/pith/JYBPAWINIB7VEIUT6GQWZE7TV2","download_json":"https://pith.science/pith/JYBPAWINIB7VEIUT6GQWZE7TV2.json","view_paper":"https://pith.science/paper/JYBPAWIN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1505.05668&json=true","fetch_graph":"https://pith.science/api/pith-number/JYBPAWINIB7VEIUT6GQWZE7TV2/graph.json","fetch_events":"https://pith.science/api/pith-number/JYBPAWINIB7VEIUT6GQWZE7TV2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JYBPAWINIB7VEIUT6GQWZE7TV2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JYBPAWINIB7VEIUT6GQWZE7TV2/action/storage_attestation","attest_author":"https://pith.science/pith/JYBPAWINIB7VEIUT6GQWZE7TV2/action/author_attestation","sign_citation":"https://pith.science/pith/JYBPAWINIB7VEIUT6GQWZE7TV2/action/citation_signature","submit_replication":"https://pith.science/pith/JYBPAWINIB7VEIUT6GQWZE7TV2/action/replication_record"}},"created_at":"2026-05-18T00:06:12.795099+00:00","updated_at":"2026-05-18T00:06:12.795099+00:00"}