{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:J2XC5AJ3A3WJZN3AIJ65D2I452","short_pith_number":"pith:J2XC5AJ3","canonical_record":{"source":{"id":"1205.3906","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2012-05-17T11:17:08Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"b34a5fc84dac7be5a931784420252872a09198c5dd3b38fa2600d3d269d79e36","abstract_canon_sha256":"b04d17e0f834424ac2a0274ef763351c412f9c0046d33c7ce6e52e946a254c83"},"schema_version":"1.0"},"canonical_sha256":"4eae2e813b06ec9cb760427dd1e91cee9f21f2946b835a2e9bfbed2808dc9731","source":{"kind":"arxiv","id":"1205.3906","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1205.3906","created_at":"2026-05-18T02:21:10Z"},{"alias_kind":"arxiv_version","alias_value":"1205.3906v3","created_at":"2026-05-18T02:21:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1205.3906","created_at":"2026-05-18T02:21:10Z"},{"alias_kind":"pith_short_12","alias_value":"J2XC5AJ3A3WJ","created_at":"2026-05-18T12:27:09Z"},{"alias_kind":"pith_short_16","alias_value":"J2XC5AJ3A3WJZN3A","created_at":"2026-05-18T12:27:09Z"},{"alias_kind":"pith_short_8","alias_value":"J2XC5AJ3","created_at":"2026-05-18T12:27:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:J2XC5AJ3A3WJZN3AIJ65D2I452","target":"record","payload":{"canonical_record":{"source":{"id":"1205.3906","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2012-05-17T11:17:08Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"b34a5fc84dac7be5a931784420252872a09198c5dd3b38fa2600d3d269d79e36","abstract_canon_sha256":"b04d17e0f834424ac2a0274ef763351c412f9c0046d33c7ce6e52e946a254c83"},"schema_version":"1.0"},"canonical_sha256":"4eae2e813b06ec9cb760427dd1e91cee9f21f2946b835a2e9bfbed2808dc9731","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:21:10.271277Z","signature_b64":"Bd3F0vUYltDjIUhW9V3QmFMCQlQI0WTuajqSR1/spCKv6Tjsc4m4d9CF0IipxeByZCNzF6BSUUwVjji+xAg7Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4eae2e813b06ec9cb760427dd1e91cee9f21f2946b835a2e9bfbed2808dc9731","last_reissued_at":"2026-05-18T02:21:10.270714Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:21:10.270714Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1205.3906","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:21:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"o/3tIptkUpQMc3IATj3oMsx3peoBOahpDX+55LdS/XMOoP4QoYeiWkQ98ntlGgSYC0BFsEDOlHFaRc+zSYimCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T21:36:12.470686Z"},"content_sha256":"ccfdf52063d2b6dfb4e6fe1432a41767739611828f96b0994d8101a8ff0e1542","schema_version":"1.0","event_id":"sha256:ccfdf52063d2b6dfb4e6fe1432a41767739611828f96b0994d8101a8ff0e1542"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:J2XC5AJ3A3WJZN3AIJ65D2I452","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Variational Inference for Generalized Linear Mixed Models Using Partially Noncentered Parametrizations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"stat.CO","authors_text":"David J. Nott, Linda S. L. Tan","submitted_at":"2012-05-17T11:17:08Z","abstract_excerpt":"The effects of different parametrizations on the convergence of Bayesian computational algorithms for hierarchical models are well explored. Techniques such as centering, noncentering and partial noncentering can be used to accelerate convergence in MCMC and EM algorithms but are still not well studied for variational Bayes (VB) methods. As a fast deterministic approach to posterior approximation, VB is attracting increasing interest due to its suitability for large high-dimensional data. Use of different parametrizations for VB has not only computational but also statistical implications, as "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1205.3906","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:21:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QMF7Hc1+QRCSbk8ucn4Pyh5QwcJw63AXaZSZ2rQkpEeH2KiFo+c50GCeBKW4aJ50KTbTT7xRaKA9ejeSaubeCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T21:36:12.471400Z"},"content_sha256":"d720bb559ab0d6a59238abc373b2d6b185f65b60b01cdf986fde050129cf0dce","schema_version":"1.0","event_id":"sha256:d720bb559ab0d6a59238abc373b2d6b185f65b60b01cdf986fde050129cf0dce"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/J2XC5AJ3A3WJZN3AIJ65D2I452/bundle.json","state_url":"https://pith.science/pith/J2XC5AJ3A3WJZN3AIJ65D2I452/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/J2XC5AJ3A3WJZN3AIJ65D2I452/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-30T21:36:12Z","links":{"resolver":"https://pith.science/pith/J2XC5AJ3A3WJZN3AIJ65D2I452","bundle":"https://pith.science/pith/J2XC5AJ3A3WJZN3AIJ65D2I452/bundle.json","state":"https://pith.science/pith/J2XC5AJ3A3WJZN3AIJ65D2I452/state.json","well_known_bundle":"https://pith.science/.well-known/pith/J2XC5AJ3A3WJZN3AIJ65D2I452/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:J2XC5AJ3A3WJZN3AIJ65D2I452","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":"b04d17e0f834424ac2a0274ef763351c412f9c0046d33c7ce6e52e946a254c83","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2012-05-17T11:17:08Z","title_canon_sha256":"b34a5fc84dac7be5a931784420252872a09198c5dd3b38fa2600d3d269d79e36"},"schema_version":"1.0","source":{"id":"1205.3906","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1205.3906","created_at":"2026-05-18T02:21:10Z"},{"alias_kind":"arxiv_version","alias_value":"1205.3906v3","created_at":"2026-05-18T02:21:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1205.3906","created_at":"2026-05-18T02:21:10Z"},{"alias_kind":"pith_short_12","alias_value":"J2XC5AJ3A3WJ","created_at":"2026-05-18T12:27:09Z"},{"alias_kind":"pith_short_16","alias_value":"J2XC5AJ3A3WJZN3A","created_at":"2026-05-18T12:27:09Z"},{"alias_kind":"pith_short_8","alias_value":"J2XC5AJ3","created_at":"2026-05-18T12:27:09Z"}],"graph_snapshots":[{"event_id":"sha256:d720bb559ab0d6a59238abc373b2d6b185f65b60b01cdf986fde050129cf0dce","target":"graph","created_at":"2026-05-18T02:21:10Z","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":"The effects of different parametrizations on the convergence of Bayesian computational algorithms for hierarchical models are well explored. Techniques such as centering, noncentering and partial noncentering can be used to accelerate convergence in MCMC and EM algorithms but are still not well studied for variational Bayes (VB) methods. As a fast deterministic approach to posterior approximation, VB is attracting increasing interest due to its suitability for large high-dimensional data. Use of different parametrizations for VB has not only computational but also statistical implications, as ","authors_text":"David J. Nott, Linda S. L. Tan","cross_cats":["stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2012-05-17T11:17:08Z","title":"Variational Inference for Generalized Linear Mixed Models Using Partially Noncentered Parametrizations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1205.3906","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:ccfdf52063d2b6dfb4e6fe1432a41767739611828f96b0994d8101a8ff0e1542","target":"record","created_at":"2026-05-18T02:21:10Z","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":"b04d17e0f834424ac2a0274ef763351c412f9c0046d33c7ce6e52e946a254c83","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2012-05-17T11:17:08Z","title_canon_sha256":"b34a5fc84dac7be5a931784420252872a09198c5dd3b38fa2600d3d269d79e36"},"schema_version":"1.0","source":{"id":"1205.3906","kind":"arxiv","version":3}},"canonical_sha256":"4eae2e813b06ec9cb760427dd1e91cee9f21f2946b835a2e9bfbed2808dc9731","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4eae2e813b06ec9cb760427dd1e91cee9f21f2946b835a2e9bfbed2808dc9731","first_computed_at":"2026-05-18T02:21:10.270714Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:21:10.270714Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Bd3F0vUYltDjIUhW9V3QmFMCQlQI0WTuajqSR1/spCKv6Tjsc4m4d9CF0IipxeByZCNzF6BSUUwVjji+xAg7Aw==","signature_status":"signed_v1","signed_at":"2026-05-18T02:21:10.271277Z","signed_message":"canonical_sha256_bytes"},"source_id":"1205.3906","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ccfdf52063d2b6dfb4e6fe1432a41767739611828f96b0994d8101a8ff0e1542","sha256:d720bb559ab0d6a59238abc373b2d6b185f65b60b01cdf986fde050129cf0dce"],"state_sha256":"e803f84f4373cdcec091ac5c35d2cd7361bfe9136f2d779ec6cd19b9c95e3637"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nuwW/koAXQs69V9x6TPC47aFB6cHpoHv6axH0kdHwbKCca4heKMLfMBIk2CdotPl4zTlq9brA0+yITS9aUA2Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T21:36:12.475815Z","bundle_sha256":"29d3cbc00a6856f5d0ab801da5699dfc5a0dd0f068e3e88de90220238c3c6fda"}}