{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:JNOIRDVYXU5PL3PEBNRERUSOY5","short_pith_number":"pith:JNOIRDVY","canonical_record":{"source":{"id":"2111.08095","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-15T21:42:14Z","cross_cats_sorted":[],"title_canon_sha256":"f51cb2fc8f69294982d4a2a7c86156f8f74848d6a98acf89c75947c4bcc266b4","abstract_canon_sha256":"e77d4f393fc74b59c3921cac6a65fdc90bfee10899d9cfb7b0cbbf728b0368e6"},"schema_version":"1.0"},"canonical_sha256":"4b5c888eb8bd3af5ede40b6248d24ec7788bd3e638b1f46e76282cc7cd5cf292","source":{"kind":"arxiv","id":"2111.08095","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.08095","created_at":"2026-07-05T03:38:40Z"},{"alias_kind":"arxiv_version","alias_value":"2111.08095v3","created_at":"2026-07-05T03:38:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.08095","created_at":"2026-07-05T03:38:40Z"},{"alias_kind":"pith_short_12","alias_value":"JNOIRDVYXU5P","created_at":"2026-07-05T03:38:40Z"},{"alias_kind":"pith_short_16","alias_value":"JNOIRDVYXU5PL3PE","created_at":"2026-07-05T03:38:40Z"},{"alias_kind":"pith_short_8","alias_value":"JNOIRDVY","created_at":"2026-07-05T03:38:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:JNOIRDVYXU5PL3PEBNRERUSOY5","target":"record","payload":{"canonical_record":{"source":{"id":"2111.08095","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-15T21:42:14Z","cross_cats_sorted":[],"title_canon_sha256":"f51cb2fc8f69294982d4a2a7c86156f8f74848d6a98acf89c75947c4bcc266b4","abstract_canon_sha256":"e77d4f393fc74b59c3921cac6a65fdc90bfee10899d9cfb7b0cbbf728b0368e6"},"schema_version":"1.0"},"canonical_sha256":"4b5c888eb8bd3af5ede40b6248d24ec7788bd3e638b1f46e76282cc7cd5cf292","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:38:40.445696Z","signature_b64":"Bs3yEv+XgO3onr9XNI4blVKhHivLsj/t/Cf6grUliBHOOGJYY1MWMgA9goxXIaJ+HB7U6cAvDq1kxunNzCXrDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4b5c888eb8bd3af5ede40b6248d24ec7788bd3e638b1f46e76282cc7cd5cf292","last_reissued_at":"2026-07-05T03:38:40.443587Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:38:40.443587Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2111.08095","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":"2026-07-05T03:38:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LC/JwlKFYW7btGOSfPafOpJrmNAsZixr4dFd6End5pN1QGmcSo6n7QtAUD9SMFMlXH2QTtmR3mfUzmNQEjTzBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-14T19:50:35.801243Z"},"content_sha256":"9282774d9f6bd8b4211a32b7084a96e39a738a6bd01a943545f835fd6a9d573f","schema_version":"1.0","event_id":"sha256:9282774d9f6bd8b4211a32b7084a96e39a738a6bd01a943545f835fd6a9d573f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:JNOIRDVYXU5PL3PEBNRERUSOY5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Abhyuday Desai, Cynthia Freeman, Ian Beaver, Zuhui Wang","submitted_at":"2021-11-15T21:42:14Z","abstract_excerpt":"Recent work in synthetic data generation in the time-series domain has focused on the use of Generative Adversarial Networks. We propose a novel architecture for synthetically generating time-series data with the use of Variational Auto-Encoders (VAEs). The proposed architecture has several distinct properties: interpretability, ability to encode domain knowledge, and reduced training times. We evaluate data generation quality by similarity and predictability against four multivariate datasets. We experiment with varying sizes of training data to measure the impact of data availability on gene"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.08095","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2111.08095/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":"2026-07-05T03:38:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ehxx5676Bb0KC6D4P8RiR6IRMUAggjcx+7GWEKKEIhukT5NHXDY9AMHXMBt1Dr22Finp1teivqDIfaoL8/ytDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-14T19:50:35.801620Z"},"content_sha256":"3ea2307726f4c419ca2c98c1f325180f35dde3472564d97ab55289a8678d7db7","schema_version":"1.0","event_id":"sha256:3ea2307726f4c419ca2c98c1f325180f35dde3472564d97ab55289a8678d7db7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JNOIRDVYXU5PL3PEBNRERUSOY5/bundle.json","state_url":"https://pith.science/pith/JNOIRDVYXU5PL3PEBNRERUSOY5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JNOIRDVYXU5PL3PEBNRERUSOY5/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":"2026-07-14T19:50:35Z","links":{"resolver":"https://pith.science/pith/JNOIRDVYXU5PL3PEBNRERUSOY5","bundle":"https://pith.science/pith/JNOIRDVYXU5PL3PEBNRERUSOY5/bundle.json","state":"https://pith.science/pith/JNOIRDVYXU5PL3PEBNRERUSOY5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JNOIRDVYXU5PL3PEBNRERUSOY5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:JNOIRDVYXU5PL3PEBNRERUSOY5","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":"e77d4f393fc74b59c3921cac6a65fdc90bfee10899d9cfb7b0cbbf728b0368e6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-15T21:42:14Z","title_canon_sha256":"f51cb2fc8f69294982d4a2a7c86156f8f74848d6a98acf89c75947c4bcc266b4"},"schema_version":"1.0","source":{"id":"2111.08095","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.08095","created_at":"2026-07-05T03:38:40Z"},{"alias_kind":"arxiv_version","alias_value":"2111.08095v3","created_at":"2026-07-05T03:38:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.08095","created_at":"2026-07-05T03:38:40Z"},{"alias_kind":"pith_short_12","alias_value":"JNOIRDVYXU5P","created_at":"2026-07-05T03:38:40Z"},{"alias_kind":"pith_short_16","alias_value":"JNOIRDVYXU5PL3PE","created_at":"2026-07-05T03:38:40Z"},{"alias_kind":"pith_short_8","alias_value":"JNOIRDVY","created_at":"2026-07-05T03:38:40Z"}],"graph_snapshots":[{"event_id":"sha256:3ea2307726f4c419ca2c98c1f325180f35dde3472564d97ab55289a8678d7db7","target":"graph","created_at":"2026-07-05T03:38:40Z","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/2111.08095/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent work in synthetic data generation in the time-series domain has focused on the use of Generative Adversarial Networks. We propose a novel architecture for synthetically generating time-series data with the use of Variational Auto-Encoders (VAEs). The proposed architecture has several distinct properties: interpretability, ability to encode domain knowledge, and reduced training times. We evaluate data generation quality by similarity and predictability against four multivariate datasets. We experiment with varying sizes of training data to measure the impact of data availability on gene","authors_text":"Abhyuday Desai, Cynthia Freeman, Ian Beaver, Zuhui Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-15T21:42:14Z","title":"TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.08095","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":"sha256:9282774d9f6bd8b4211a32b7084a96e39a738a6bd01a943545f835fd6a9d573f","target":"record","created_at":"2026-07-05T03:38:40Z","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":"e77d4f393fc74b59c3921cac6a65fdc90bfee10899d9cfb7b0cbbf728b0368e6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-15T21:42:14Z","title_canon_sha256":"f51cb2fc8f69294982d4a2a7c86156f8f74848d6a98acf89c75947c4bcc266b4"},"schema_version":"1.0","source":{"id":"2111.08095","kind":"arxiv","version":3}},"canonical_sha256":"4b5c888eb8bd3af5ede40b6248d24ec7788bd3e638b1f46e76282cc7cd5cf292","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4b5c888eb8bd3af5ede40b6248d24ec7788bd3e638b1f46e76282cc7cd5cf292","first_computed_at":"2026-07-05T03:38:40.443587Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:38:40.443587Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Bs3yEv+XgO3onr9XNI4blVKhHivLsj/t/Cf6grUliBHOOGJYY1MWMgA9goxXIaJ+HB7U6cAvDq1kxunNzCXrDw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:38:40.445696Z","signed_message":"canonical_sha256_bytes"},"source_id":"2111.08095","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9282774d9f6bd8b4211a32b7084a96e39a738a6bd01a943545f835fd6a9d573f","sha256:3ea2307726f4c419ca2c98c1f325180f35dde3472564d97ab55289a8678d7db7"],"state_sha256":"f2cd2195260347f13f717c529d47f9e8c65be71538007831888d7e46459f5945"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QEQTbes6+hEAX6uwJjKBxu9rAshdrA6sn2Z0bKqHmxgksTE2u3IvxHIoHgcgKMbit5B9kKekRl+9Rrw5IPWSAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-14T19:50:35.803733Z","bundle_sha256":"abdbd307cd4ce42fd9d4c307244e0cb7c2c1b98784bd4a449a41e6b9131b1b9b"}}