{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:ATU7I26TMLTB6JCSAOP7XBZZZO","short_pith_number":"pith:ATU7I26T","canonical_record":{"source":{"id":"1802.04537","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-13T10:17:32Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e20ded65752ad77a9999b45c243f22e41db137b452de61f05e85894d159918ae","abstract_canon_sha256":"e1522295b966600ccca19636792720812a5dd96691e99bc175ca0677ec572209"},"schema_version":"1.0"},"canonical_sha256":"04e9f46bd362e61f2452039ffb8739cbb5a08c93377ccaa9a8d7ab6839b32dfd","source":{"kind":"arxiv","id":"1802.04537","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.04537","created_at":"2026-05-17T23:51:59Z"},{"alias_kind":"arxiv_version","alias_value":"1802.04537v3","created_at":"2026-05-17T23:51:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.04537","created_at":"2026-05-17T23:51:59Z"},{"alias_kind":"pith_short_12","alias_value":"ATU7I26TMLTB","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"ATU7I26TMLTB6JCS","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"ATU7I26T","created_at":"2026-05-18T12:32:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:ATU7I26TMLTB6JCSAOP7XBZZZO","target":"record","payload":{"canonical_record":{"source":{"id":"1802.04537","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-13T10:17:32Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e20ded65752ad77a9999b45c243f22e41db137b452de61f05e85894d159918ae","abstract_canon_sha256":"e1522295b966600ccca19636792720812a5dd96691e99bc175ca0677ec572209"},"schema_version":"1.0"},"canonical_sha256":"04e9f46bd362e61f2452039ffb8739cbb5a08c93377ccaa9a8d7ab6839b32dfd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:51:59.082752Z","signature_b64":"e6F28w9Awfs6EAWGPJA+lUVJrl2TA80VdY8JeUlOzxpj3GWIDR92gt3VErXv5yAoZqqkneZvoBQ2LVb+oaMnAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"04e9f46bd362e61f2452039ffb8739cbb5a08c93377ccaa9a8d7ab6839b32dfd","last_reissued_at":"2026-05-17T23:51:59.082365Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:51:59.082365Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.04537","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":"2026-05-17T23:51:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X6sDDnFB8tWFv94I37wXgKCxH+CWkm2tS8FfxVHLynLiMeDfljlItTSHiku2qd87isZTl7kXOZH95a2lim2iCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T05:43:30.275908Z"},"content_sha256":"092269314f5a640c4b1ff87cb926594583ca22ddff791dd1fc73c6312ae6aeca","schema_version":"1.0","event_id":"sha256:092269314f5a640c4b1ff87cb926594583ca22ddff791dd1fc73c6312ae6aeca"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:ATU7I26TMLTB6JCSAOP7XBZZZO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Tighter Variational Bounds are Not Necessarily Better","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Adam R. Kosiorek, Chris J. Maddison, Frank Wood, Maximilian Igl, Tom Rainforth, Tuan Anh Le, Yee Whye Teh","submitted_at":"2018-02-13T10:17:32Z","abstract_excerpt":"We provide theoretical and empirical evidence that using tighter evidence lower bounds (ELBOs) can be detrimental to the process of learning an inference network by reducing the signal-to-noise ratio of the gradient estimator. Our results call into question common implicit assumptions that tighter ELBOs are better variational objectives for simultaneous model learning and inference amortization schemes. Based on our insights, we introduce three new algorithms: the partially importance weighted auto-encoder (PIWAE), the multiply importance weighted auto-encoder (MIWAE), and the combination impo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.04537","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":"2026-05-17T23:51:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2oITQAETCIJCSnlt7P+QXen7MdQr2+HBviJ6zQx1gwcPU00FI64nwwcyFZvXd8Po6hnR6EAGP2mYoYbnikRgDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T05:43:30.276250Z"},"content_sha256":"412172f4020aa1bd406a7f9ee180b0ec7a730cf2fcf85f4ce5e7fbedab4a4d79","schema_version":"1.0","event_id":"sha256:412172f4020aa1bd406a7f9ee180b0ec7a730cf2fcf85f4ce5e7fbedab4a4d79"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ATU7I26TMLTB6JCSAOP7XBZZZO/bundle.json","state_url":"https://pith.science/pith/ATU7I26TMLTB6JCSAOP7XBZZZO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ATU7I26TMLTB6JCSAOP7XBZZZO/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":"2026-05-28T05:43:30Z","links":{"resolver":"https://pith.science/pith/ATU7I26TMLTB6JCSAOP7XBZZZO","bundle":"https://pith.science/pith/ATU7I26TMLTB6JCSAOP7XBZZZO/bundle.json","state":"https://pith.science/pith/ATU7I26TMLTB6JCSAOP7XBZZZO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ATU7I26TMLTB6JCSAOP7XBZZZO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:ATU7I26TMLTB6JCSAOP7XBZZZO","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":"e1522295b966600ccca19636792720812a5dd96691e99bc175ca0677ec572209","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-13T10:17:32Z","title_canon_sha256":"e20ded65752ad77a9999b45c243f22e41db137b452de61f05e85894d159918ae"},"schema_version":"1.0","source":{"id":"1802.04537","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.04537","created_at":"2026-05-17T23:51:59Z"},{"alias_kind":"arxiv_version","alias_value":"1802.04537v3","created_at":"2026-05-17T23:51:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.04537","created_at":"2026-05-17T23:51:59Z"},{"alias_kind":"pith_short_12","alias_value":"ATU7I26TMLTB","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"ATU7I26TMLTB6JCS","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"ATU7I26T","created_at":"2026-05-18T12:32:13Z"}],"graph_snapshots":[{"event_id":"sha256:412172f4020aa1bd406a7f9ee180b0ec7a730cf2fcf85f4ce5e7fbedab4a4d79","target":"graph","created_at":"2026-05-17T23:51:59Z","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":"We provide theoretical and empirical evidence that using tighter evidence lower bounds (ELBOs) can be detrimental to the process of learning an inference network by reducing the signal-to-noise ratio of the gradient estimator. Our results call into question common implicit assumptions that tighter ELBOs are better variational objectives for simultaneous model learning and inference amortization schemes. Based on our insights, we introduce three new algorithms: the partially importance weighted auto-encoder (PIWAE), the multiply importance weighted auto-encoder (MIWAE), and the combination impo","authors_text":"Adam R. Kosiorek, Chris J. Maddison, Frank Wood, Maximilian Igl, Tom Rainforth, Tuan Anh Le, Yee Whye Teh","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-13T10:17:32Z","title":"Tighter Variational Bounds are Not Necessarily Better"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.04537","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":"sha256:092269314f5a640c4b1ff87cb926594583ca22ddff791dd1fc73c6312ae6aeca","target":"record","created_at":"2026-05-17T23:51:59Z","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":"e1522295b966600ccca19636792720812a5dd96691e99bc175ca0677ec572209","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-13T10:17:32Z","title_canon_sha256":"e20ded65752ad77a9999b45c243f22e41db137b452de61f05e85894d159918ae"},"schema_version":"1.0","source":{"id":"1802.04537","kind":"arxiv","version":3}},"canonical_sha256":"04e9f46bd362e61f2452039ffb8739cbb5a08c93377ccaa9a8d7ab6839b32dfd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"04e9f46bd362e61f2452039ffb8739cbb5a08c93377ccaa9a8d7ab6839b32dfd","first_computed_at":"2026-05-17T23:51:59.082365Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:51:59.082365Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"e6F28w9Awfs6EAWGPJA+lUVJrl2TA80VdY8JeUlOzxpj3GWIDR92gt3VErXv5yAoZqqkneZvoBQ2LVb+oaMnAA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:51:59.082752Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.04537","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:092269314f5a640c4b1ff87cb926594583ca22ddff791dd1fc73c6312ae6aeca","sha256:412172f4020aa1bd406a7f9ee180b0ec7a730cf2fcf85f4ce5e7fbedab4a4d79"],"state_sha256":"11dd7cc64a84438b6a90652b65d17a7f446a2e17d79abc53f68258dac7aaf8f0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TUw+oEI30enBHegx4R2qKEF8lT5HYKBiE8RrZ1JHpNdk2maeMeB/8+94J8rS2ow9rASodXjA1rKCc8SnDeD9DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T05:43:30.278212Z","bundle_sha256":"d78a61872b100b2a7f189cecafb5dd0b07c882d66fafb1217b6fdb5f45829c44"}}