{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:G7DGZDJYIHJX5O45NFKPL7PIQ4","short_pith_number":"pith:G7DGZDJY","canonical_record":{"source":{"id":"2312.06591","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2023-12-11T18:27:25Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"07c38b73a1a8df5e9d8ae3c49193ca0a9f1ce88462016dd3443b9b700f3113ad","abstract_canon_sha256":"d0178f453ac497f94ca89b7f774509d722346e83faf0d9ca8eaf5596d1a20265"},"schema_version":"1.0"},"canonical_sha256":"37c66c8d3841d37ebb9d6954f5fde887134c58e216cfaa7b6cebf1412225d914","source":{"kind":"arxiv","id":"2312.06591","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.06591","created_at":"2026-07-05T07:22:47Z"},{"alias_kind":"arxiv_version","alias_value":"2312.06591v1","created_at":"2026-07-05T07:22:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.06591","created_at":"2026-07-05T07:22:47Z"},{"alias_kind":"pith_short_12","alias_value":"G7DGZDJYIHJX","created_at":"2026-07-05T07:22:47Z"},{"alias_kind":"pith_short_16","alias_value":"G7DGZDJYIHJX5O45","created_at":"2026-07-05T07:22:47Z"},{"alias_kind":"pith_short_8","alias_value":"G7DGZDJY","created_at":"2026-07-05T07:22:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:G7DGZDJYIHJX5O45NFKPL7PIQ4","target":"record","payload":{"canonical_record":{"source":{"id":"2312.06591","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2023-12-11T18:27:25Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"07c38b73a1a8df5e9d8ae3c49193ca0a9f1ce88462016dd3443b9b700f3113ad","abstract_canon_sha256":"d0178f453ac497f94ca89b7f774509d722346e83faf0d9ca8eaf5596d1a20265"},"schema_version":"1.0"},"canonical_sha256":"37c66c8d3841d37ebb9d6954f5fde887134c58e216cfaa7b6cebf1412225d914","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:22:47.400539Z","signature_b64":"RbF64gfhTwIHlFCdZpmMRX+Sty6gpzX2iizAix0tNt6dI6vFyNgkxFZu3AUFdKdK7rEJ6Prrn5tCn32rOX1MAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"37c66c8d3841d37ebb9d6954f5fde887134c58e216cfaa7b6cebf1412225d914","last_reissued_at":"2026-07-05T07:22:47.400020Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:22:47.400020Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.06591","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:22:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Rq8C7gKl/05TojNeGFeK3wOjE8iK1X06kfUjIcsErH9sukDRBiAOi0B88J/WRFuOmg3NCb9MkuGUo/LbhvWFCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T12:40:20.293443Z"},"content_sha256":"f5efbc9fb868d35b78ed8010597e3df80858df8ece72ca1c0242a0970cc2934e","schema_version":"1.0","event_id":"sha256:f5efbc9fb868d35b78ed8010597e3df80858df8ece72ca1c0242a0970cc2934e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:G7DGZDJYIHJX5O45NFKPL7PIQ4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Concurrent Density Estimation with Wasserstein Autoencoders: Some Statistical Insights","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Anish Chakrabarty, Arkaprabha Basu, Swagatam Das","submitted_at":"2023-12-11T18:27:25Z","abstract_excerpt":"Variational Autoencoders (VAEs) have been a pioneering force in the realm of deep generative models. Amongst its legions of progenies, Wasserstein Autoencoders (WAEs) stand out in particular due to the dual offering of heightened generative quality and a strong theoretical backbone. WAEs consist of an encoding and a decoding network forming a bottleneck with the prime objective of generating new samples resembling the ones it was catered to. In the process, they aim to achieve a target latent representation of the encoded data. Our work is an attempt to offer a theoretical understanding of the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.06591","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2312.06591/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":"2026-07-05T07:22:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BUfc7JYvw1rAfA2mvVHkcdlPyPoFCiJJXNi2dsYpKcd9xAvINWLEEKfsc3ZpCAOitbb+C8pUFVsSyyFx+hx9Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T12:40:20.293980Z"},"content_sha256":"ef7fcc4e2d2a2bf8dc17252009ddf6197dc5d3505c2ea99cadf64fd21bcb9301","schema_version":"1.0","event_id":"sha256:ef7fcc4e2d2a2bf8dc17252009ddf6197dc5d3505c2ea99cadf64fd21bcb9301"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G7DGZDJYIHJX5O45NFKPL7PIQ4/bundle.json","state_url":"https://pith.science/pith/G7DGZDJYIHJX5O45NFKPL7PIQ4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G7DGZDJYIHJX5O45NFKPL7PIQ4/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":"2026-08-12T12:40:20Z","links":{"resolver":"https://pith.science/pith/G7DGZDJYIHJX5O45NFKPL7PIQ4","bundle":"https://pith.science/pith/G7DGZDJYIHJX5O45NFKPL7PIQ4/bundle.json","state":"https://pith.science/pith/G7DGZDJYIHJX5O45NFKPL7PIQ4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G7DGZDJYIHJX5O45NFKPL7PIQ4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:G7DGZDJYIHJX5O45NFKPL7PIQ4","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":"d0178f453ac497f94ca89b7f774509d722346e83faf0d9ca8eaf5596d1a20265","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2023-12-11T18:27:25Z","title_canon_sha256":"07c38b73a1a8df5e9d8ae3c49193ca0a9f1ce88462016dd3443b9b700f3113ad"},"schema_version":"1.0","source":{"id":"2312.06591","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.06591","created_at":"2026-07-05T07:22:47Z"},{"alias_kind":"arxiv_version","alias_value":"2312.06591v1","created_at":"2026-07-05T07:22:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.06591","created_at":"2026-07-05T07:22:47Z"},{"alias_kind":"pith_short_12","alias_value":"G7DGZDJYIHJX","created_at":"2026-07-05T07:22:47Z"},{"alias_kind":"pith_short_16","alias_value":"G7DGZDJYIHJX5O45","created_at":"2026-07-05T07:22:47Z"},{"alias_kind":"pith_short_8","alias_value":"G7DGZDJY","created_at":"2026-07-05T07:22:47Z"}],"graph_snapshots":[{"event_id":"sha256:ef7fcc4e2d2a2bf8dc17252009ddf6197dc5d3505c2ea99cadf64fd21bcb9301","target":"graph","created_at":"2026-07-05T07:22:47Z","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/2312.06591/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Variational Autoencoders (VAEs) have been a pioneering force in the realm of deep generative models. Amongst its legions of progenies, Wasserstein Autoencoders (WAEs) stand out in particular due to the dual offering of heightened generative quality and a strong theoretical backbone. WAEs consist of an encoding and a decoding network forming a bottleneck with the prime objective of generating new samples resembling the ones it was catered to. In the process, they aim to achieve a target latent representation of the encoded data. Our work is an attempt to offer a theoretical understanding of the","authors_text":"Anish Chakrabarty, Arkaprabha Basu, Swagatam Das","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2023-12-11T18:27:25Z","title":"Concurrent Density Estimation with Wasserstein Autoencoders: Some Statistical Insights"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.06591","kind":"arxiv","version":1},"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:f5efbc9fb868d35b78ed8010597e3df80858df8ece72ca1c0242a0970cc2934e","target":"record","created_at":"2026-07-05T07:22:47Z","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":"d0178f453ac497f94ca89b7f774509d722346e83faf0d9ca8eaf5596d1a20265","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2023-12-11T18:27:25Z","title_canon_sha256":"07c38b73a1a8df5e9d8ae3c49193ca0a9f1ce88462016dd3443b9b700f3113ad"},"schema_version":"1.0","source":{"id":"2312.06591","kind":"arxiv","version":1}},"canonical_sha256":"37c66c8d3841d37ebb9d6954f5fde887134c58e216cfaa7b6cebf1412225d914","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"37c66c8d3841d37ebb9d6954f5fde887134c58e216cfaa7b6cebf1412225d914","first_computed_at":"2026-07-05T07:22:47.400020Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:22:47.400020Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RbF64gfhTwIHlFCdZpmMRX+Sty6gpzX2iizAix0tNt6dI6vFyNgkxFZu3AUFdKdK7rEJ6Prrn5tCn32rOX1MAw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:22:47.400539Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.06591","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f5efbc9fb868d35b78ed8010597e3df80858df8ece72ca1c0242a0970cc2934e","sha256:ef7fcc4e2d2a2bf8dc17252009ddf6197dc5d3505c2ea99cadf64fd21bcb9301"],"state_sha256":"ae033e415066c265894292f72ff80fde903be4e6cf80570a3b5eb91b02ecead4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b3wIqzN89O27ZEpOo78Xb5fv//9hgKmDNRZ9uUOYTzs+4qp9a+zoC0XWcW6Jv13eglfUyMOUCspvhH//ECvYCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T12:40:20.298362Z","bundle_sha256":"1173a632cfecc1aa5bba3bded6a3bdfae351c4c1f8b024bad2fde13436c17948"}}