{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:WOEGBVJQTFRLSKQU73RILQSOJN","short_pith_number":"pith:WOEGBVJQ","schema_version":"1.0","canonical_sha256":"b38860d5309962b92a14fee285c24e4b42ce69cc76410d4029ee4abf387f608c","source":{"kind":"arxiv","id":"1409.7074","version":1},"attestation_state":"computed","paper":{"title":"Variational Pseudolikelihood for Regularized Ising Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cond-mat.stat-mech","authors_text":"Charles K. Fisher","submitted_at":"2014-09-24T20:01:15Z","abstract_excerpt":"I propose a variational approach to maximum pseudolikelihood inference of the Ising model. The variational algorithm is more computationally efficient, and does a better job predicting out-of-sample correlations than $L_2$ regularized maximum pseudolikelihood inference as well as mean field and isolated spin pair approximations with pseudocount regularization. The key to the approach is a variational energy that regularizes the inference problem by shrinking the couplings towards zero, while still allowing some large couplings to explain strong correlations. The utility of the variational pseu"},"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":"1409.7074","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.stat-mech","submitted_at":"2014-09-24T20:01:15Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"66f72191beaf30ff5bda49d081a9acfbe20c6c83c0bb95b9ecc23fbacb77420f","abstract_canon_sha256":"568610438239d0b35c90beeb015340c79c6fb5c232956147681b271a9b299aeb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:41:59.179463Z","signature_b64":"0J3Xj/ApsAHl3v0a9cb0H7PIw77Ojs4Fh6+Hgn1phiV7vfyXi28Ohy7I5JoDzV/0QqTqx1wXTw2di9bVfVOEBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b38860d5309962b92a14fee285c24e4b42ce69cc76410d4029ee4abf387f608c","last_reissued_at":"2026-05-18T02:41:59.179103Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:41:59.179103Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Variational Pseudolikelihood for Regularized Ising Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cond-mat.stat-mech","authors_text":"Charles K. Fisher","submitted_at":"2014-09-24T20:01:15Z","abstract_excerpt":"I propose a variational approach to maximum pseudolikelihood inference of the Ising model. The variational algorithm is more computationally efficient, and does a better job predicting out-of-sample correlations than $L_2$ regularized maximum pseudolikelihood inference as well as mean field and isolated spin pair approximations with pseudocount regularization. The key to the approach is a variational energy that regularizes the inference problem by shrinking the couplings towards zero, while still allowing some large couplings to explain strong correlations. The utility of the variational pseu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1409.7074","kind":"arxiv","version":1},"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":"1409.7074","created_at":"2026-05-18T02:41:59.179155+00:00"},{"alias_kind":"arxiv_version","alias_value":"1409.7074v1","created_at":"2026-05-18T02:41:59.179155+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1409.7074","created_at":"2026-05-18T02:41:59.179155+00:00"},{"alias_kind":"pith_short_12","alias_value":"WOEGBVJQTFRL","created_at":"2026-05-18T12:28:54.890064+00:00"},{"alias_kind":"pith_short_16","alias_value":"WOEGBVJQTFRLSKQU","created_at":"2026-05-18T12:28:54.890064+00:00"},{"alias_kind":"pith_short_8","alias_value":"WOEGBVJQ","created_at":"2026-05-18T12:28:54.890064+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/WOEGBVJQTFRLSKQU73RILQSOJN","json":"https://pith.science/pith/WOEGBVJQTFRLSKQU73RILQSOJN.json","graph_json":"https://pith.science/api/pith-number/WOEGBVJQTFRLSKQU73RILQSOJN/graph.json","events_json":"https://pith.science/api/pith-number/WOEGBVJQTFRLSKQU73RILQSOJN/events.json","paper":"https://pith.science/paper/WOEGBVJQ"},"agent_actions":{"view_html":"https://pith.science/pith/WOEGBVJQTFRLSKQU73RILQSOJN","download_json":"https://pith.science/pith/WOEGBVJQTFRLSKQU73RILQSOJN.json","view_paper":"https://pith.science/paper/WOEGBVJQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1409.7074&json=true","fetch_graph":"https://pith.science/api/pith-number/WOEGBVJQTFRLSKQU73RILQSOJN/graph.json","fetch_events":"https://pith.science/api/pith-number/WOEGBVJQTFRLSKQU73RILQSOJN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WOEGBVJQTFRLSKQU73RILQSOJN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WOEGBVJQTFRLSKQU73RILQSOJN/action/storage_attestation","attest_author":"https://pith.science/pith/WOEGBVJQTFRLSKQU73RILQSOJN/action/author_attestation","sign_citation":"https://pith.science/pith/WOEGBVJQTFRLSKQU73RILQSOJN/action/citation_signature","submit_replication":"https://pith.science/pith/WOEGBVJQTFRLSKQU73RILQSOJN/action/replication_record"}},"created_at":"2026-05-18T02:41:59.179155+00:00","updated_at":"2026-05-18T02:41:59.179155+00:00"}