{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:Z2AKT3VIQ56GUTJXN77NO4BMO7","short_pith_number":"pith:Z2AKT3VI","schema_version":"1.0","canonical_sha256":"ce80a9eea8877c6a4d376ffed7702c77c4df6e6a651ce2fbedf4444c936ebebd","source":{"kind":"arxiv","id":"1605.06544","version":1},"attestation_state":"computed","paper":{"title":"Inference by Reparameterization in Neural Population Codes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.NC","authors_text":"Rajkumar Vasudeva Raju, Xaq Pitkow","submitted_at":"2016-05-20T21:38:32Z","abstract_excerpt":"Behavioral experiments on humans and animals suggest that the brain performs probabilistic inference to interpret its environment. Here we present a new general-purpose, biologically-plausible neural implementation of approximate inference. The neural network represents uncertainty using Probabilistic Population Codes (PPCs), which are distributed neural representations that naturally encode probability distributions, and support marginalization and evidence integration in a biologically-plausible manner. By connecting multiple PPCs together as a probabilistic graphical model, we represent mul"},"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":"1605.06544","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2016-05-20T21:38:32Z","cross_cats_sorted":[],"title_canon_sha256":"23b6a99d583603f8619f266ef498ccc06fd7d02c984d1b04cec19fd88d9d2c1d","abstract_canon_sha256":"0f7a38ccc75e4a920580b25c27e5b8dc068b2c4bf4637cb0e5b5fec4f473b1b2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:14:11.923997Z","signature_b64":"J4wQAQ0mijKn+Ay/UcD7XdFRrS6LiBGnzhlIjctVIBZLBR0nP1zvoYpufMO8XVSiuiCBbmRfghlP3JnToJVrBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ce80a9eea8877c6a4d376ffed7702c77c4df6e6a651ce2fbedf4444c936ebebd","last_reissued_at":"2026-05-18T01:14:11.923333Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:14:11.923333Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Inference by Reparameterization in Neural Population Codes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.NC","authors_text":"Rajkumar Vasudeva Raju, Xaq Pitkow","submitted_at":"2016-05-20T21:38:32Z","abstract_excerpt":"Behavioral experiments on humans and animals suggest that the brain performs probabilistic inference to interpret its environment. Here we present a new general-purpose, biologically-plausible neural implementation of approximate inference. The neural network represents uncertainty using Probabilistic Population Codes (PPCs), which are distributed neural representations that naturally encode probability distributions, and support marginalization and evidence integration in a biologically-plausible manner. By connecting multiple PPCs together as a probabilistic graphical model, we represent mul"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.06544","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":"1605.06544","created_at":"2026-05-18T01:14:11.923426+00:00"},{"alias_kind":"arxiv_version","alias_value":"1605.06544v1","created_at":"2026-05-18T01:14:11.923426+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.06544","created_at":"2026-05-18T01:14:11.923426+00:00"},{"alias_kind":"pith_short_12","alias_value":"Z2AKT3VIQ56G","created_at":"2026-05-18T12:30:53.716459+00:00"},{"alias_kind":"pith_short_16","alias_value":"Z2AKT3VIQ56GUTJX","created_at":"2026-05-18T12:30:53.716459+00:00"},{"alias_kind":"pith_short_8","alias_value":"Z2AKT3VI","created_at":"2026-05-18T12:30:53.716459+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/Z2AKT3VIQ56GUTJXN77NO4BMO7","json":"https://pith.science/pith/Z2AKT3VIQ56GUTJXN77NO4BMO7.json","graph_json":"https://pith.science/api/pith-number/Z2AKT3VIQ56GUTJXN77NO4BMO7/graph.json","events_json":"https://pith.science/api/pith-number/Z2AKT3VIQ56GUTJXN77NO4BMO7/events.json","paper":"https://pith.science/paper/Z2AKT3VI"},"agent_actions":{"view_html":"https://pith.science/pith/Z2AKT3VIQ56GUTJXN77NO4BMO7","download_json":"https://pith.science/pith/Z2AKT3VIQ56GUTJXN77NO4BMO7.json","view_paper":"https://pith.science/paper/Z2AKT3VI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1605.06544&json=true","fetch_graph":"https://pith.science/api/pith-number/Z2AKT3VIQ56GUTJXN77NO4BMO7/graph.json","fetch_events":"https://pith.science/api/pith-number/Z2AKT3VIQ56GUTJXN77NO4BMO7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/Z2AKT3VIQ56GUTJXN77NO4BMO7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/Z2AKT3VIQ56GUTJXN77NO4BMO7/action/storage_attestation","attest_author":"https://pith.science/pith/Z2AKT3VIQ56GUTJXN77NO4BMO7/action/author_attestation","sign_citation":"https://pith.science/pith/Z2AKT3VIQ56GUTJXN77NO4BMO7/action/citation_signature","submit_replication":"https://pith.science/pith/Z2AKT3VIQ56GUTJXN77NO4BMO7/action/replication_record"}},"created_at":"2026-05-18T01:14:11.923426+00:00","updated_at":"2026-05-18T01:14:11.923426+00:00"}