{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:TDCINUVLWXONE2WLQYCESLAQOG","short_pith_number":"pith:TDCINUVL","canonical_record":{"source":{"id":"2405.19681","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-05-30T04:27:36Z","cross_cats_sorted":["cs.LG","stat.CO"],"title_canon_sha256":"fcf6a5ef14d1d434e7baf86e59161bc3c88c26eced103614d86b4fe3ace999af","abstract_canon_sha256":"249ca6bbe0cc41e0988e793700997cc7bfcf07ec8a958de4c6bfb367cf54686b"},"schema_version":"1.0"},"canonical_sha256":"98c486d2abb5dcd26acb8604492c1071823ef55a91a7550c18c47001531ddda5","source":{"kind":"arxiv","id":"2405.19681","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.19681","created_at":"2026-07-05T09:28:50Z"},{"alias_kind":"arxiv_version","alias_value":"2405.19681v2","created_at":"2026-07-05T09:28:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.19681","created_at":"2026-07-05T09:28:50Z"},{"alias_kind":"pith_short_12","alias_value":"TDCINUVLWXON","created_at":"2026-07-05T09:28:50Z"},{"alias_kind":"pith_short_16","alias_value":"TDCINUVLWXONE2WL","created_at":"2026-07-05T09:28:50Z"},{"alias_kind":"pith_short_8","alias_value":"TDCINUVL","created_at":"2026-07-05T09:28:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:TDCINUVLWXONE2WLQYCESLAQOG","target":"record","payload":{"canonical_record":{"source":{"id":"2405.19681","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-05-30T04:27:36Z","cross_cats_sorted":["cs.LG","stat.CO"],"title_canon_sha256":"fcf6a5ef14d1d434e7baf86e59161bc3c88c26eced103614d86b4fe3ace999af","abstract_canon_sha256":"249ca6bbe0cc41e0988e793700997cc7bfcf07ec8a958de4c6bfb367cf54686b"},"schema_version":"1.0"},"canonical_sha256":"98c486d2abb5dcd26acb8604492c1071823ef55a91a7550c18c47001531ddda5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:28:50.633138Z","signature_b64":"bF16xu1s8ClcmJZ/E/FFMl64Bs93AEkn0Vq5Dwygu5Ss+GQVreevpELjBosdKX3Q7rQeRt1D1SheeDfGYPnGCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"98c486d2abb5dcd26acb8604492c1071823ef55a91a7550c18c47001531ddda5","last_reissued_at":"2026-07-05T09:28:50.632642Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:28:50.632642Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.19681","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:28:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R5mprxLnFyRtYX6KbWr4izz/s+G7gZvYEqN1QvS+L+Ee3/X3YpZuIBXgzSmeQ0aSwZOftJd96ne93oqJ57kxAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T10:41:13.481693Z"},"content_sha256":"cb40251357681a955819197d9170376a8fdefc3694d81a67cf852cf4da44bdcc","schema_version":"1.0","event_id":"sha256:cb40251357681a955819197d9170376a8fdefc3694d81a67cf852cf4da44bdcc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:TDCINUVLWXONE2WLQYCESLAQOG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian Online Natural Gradient (BONG)","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","stat.CO"],"primary_cat":"stat.ML","authors_text":"Kevin Murphy, Matt Jones, Peter Chang","submitted_at":"2024-05-30T04:27:36Z","abstract_excerpt":"We propose a novel approach to sequential Bayesian inference based on variational Bayes (VB). The key insight is that, in the online setting, we do not need to add the KL term to regularize to the prior (which comes from the posterior at the previous timestep); instead we can optimize just the expected log-likelihood, performing a single step of natural gradient descent starting at the prior predictive. We prove this method recovers exact Bayesian inference if the model is conjugate. We also show how to compute an efficient deterministic approximation to the VB objective, as well as our simpli"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.19681","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2405.19681/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T09:28:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lpeGwLwdJrEnYcOIuD3HvSeYu4+ug5D4CY3p565zw3t83SHQ5CxFJ6Y6Yb1O9Jsqs0y02+N0dTqNl1uX+AVXDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T10:41:13.482195Z"},"content_sha256":"6133a862ba1843ee8bbf3d7ac7d359c16b3c169040be9f43523bcb3e9f2bc3b8","schema_version":"1.0","event_id":"sha256:6133a862ba1843ee8bbf3d7ac7d359c16b3c169040be9f43523bcb3e9f2bc3b8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TDCINUVLWXONE2WLQYCESLAQOG/bundle.json","state_url":"https://pith.science/pith/TDCINUVLWXONE2WLQYCESLAQOG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TDCINUVLWXONE2WLQYCESLAQOG/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":"2026-08-15T10:41:13Z","links":{"resolver":"https://pith.science/pith/TDCINUVLWXONE2WLQYCESLAQOG","bundle":"https://pith.science/pith/TDCINUVLWXONE2WLQYCESLAQOG/bundle.json","state":"https://pith.science/pith/TDCINUVLWXONE2WLQYCESLAQOG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TDCINUVLWXONE2WLQYCESLAQOG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:TDCINUVLWXONE2WLQYCESLAQOG","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":"249ca6bbe0cc41e0988e793700997cc7bfcf07ec8a958de4c6bfb367cf54686b","cross_cats_sorted":["cs.LG","stat.CO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-05-30T04:27:36Z","title_canon_sha256":"fcf6a5ef14d1d434e7baf86e59161bc3c88c26eced103614d86b4fe3ace999af"},"schema_version":"1.0","source":{"id":"2405.19681","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.19681","created_at":"2026-07-05T09:28:50Z"},{"alias_kind":"arxiv_version","alias_value":"2405.19681v2","created_at":"2026-07-05T09:28:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.19681","created_at":"2026-07-05T09:28:50Z"},{"alias_kind":"pith_short_12","alias_value":"TDCINUVLWXON","created_at":"2026-07-05T09:28:50Z"},{"alias_kind":"pith_short_16","alias_value":"TDCINUVLWXONE2WL","created_at":"2026-07-05T09:28:50Z"},{"alias_kind":"pith_short_8","alias_value":"TDCINUVL","created_at":"2026-07-05T09:28:50Z"}],"graph_snapshots":[{"event_id":"sha256:6133a862ba1843ee8bbf3d7ac7d359c16b3c169040be9f43523bcb3e9f2bc3b8","target":"graph","created_at":"2026-07-05T09:28:50Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2405.19681/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose a novel approach to sequential Bayesian inference based on variational Bayes (VB). The key insight is that, in the online setting, we do not need to add the KL term to regularize to the prior (which comes from the posterior at the previous timestep); instead we can optimize just the expected log-likelihood, performing a single step of natural gradient descent starting at the prior predictive. We prove this method recovers exact Bayesian inference if the model is conjugate. We also show how to compute an efficient deterministic approximation to the VB objective, as well as our simpli","authors_text":"Kevin Murphy, Matt Jones, Peter Chang","cross_cats":["cs.LG","stat.CO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-05-30T04:27:36Z","title":"Bayesian Online Natural Gradient (BONG)"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.19681","kind":"arxiv","version":2},"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:cb40251357681a955819197d9170376a8fdefc3694d81a67cf852cf4da44bdcc","target":"record","created_at":"2026-07-05T09:28:50Z","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":"249ca6bbe0cc41e0988e793700997cc7bfcf07ec8a958de4c6bfb367cf54686b","cross_cats_sorted":["cs.LG","stat.CO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-05-30T04:27:36Z","title_canon_sha256":"fcf6a5ef14d1d434e7baf86e59161bc3c88c26eced103614d86b4fe3ace999af"},"schema_version":"1.0","source":{"id":"2405.19681","kind":"arxiv","version":2}},"canonical_sha256":"98c486d2abb5dcd26acb8604492c1071823ef55a91a7550c18c47001531ddda5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"98c486d2abb5dcd26acb8604492c1071823ef55a91a7550c18c47001531ddda5","first_computed_at":"2026-07-05T09:28:50.632642Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:28:50.632642Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bF16xu1s8ClcmJZ/E/FFMl64Bs93AEkn0Vq5Dwygu5Ss+GQVreevpELjBosdKX3Q7rQeRt1D1SheeDfGYPnGCg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:28:50.633138Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.19681","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cb40251357681a955819197d9170376a8fdefc3694d81a67cf852cf4da44bdcc","sha256:6133a862ba1843ee8bbf3d7ac7d359c16b3c169040be9f43523bcb3e9f2bc3b8"],"state_sha256":"9599f433b27b1131233d9f9441694818b72903fcab1be3799e4ecb6cb8b509bc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wzC7cZcgQgOaCxutBMWGpflXdCel5+iZ9PNlu3vSxqSfxg3btM2Oo8LYQQ2sJRchtmJ23pmYs9RVh7zytpNtBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T10:41:13.486706Z","bundle_sha256":"0039d049c5a3e26a2b2abe001ee5c5a5bb872a0710345defbaf356f1e45087aa"}}