{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:L443YTVROE7DOEN4GBNPZQCCHB","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":"ffd7d483e5f79d7baafc59ca0665a27dd4b81c4f36c543116178764c9a44f777","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2022-05-23T10:04:21Z","title_canon_sha256":"f4ea4f0fc91d6ed746843960893829727ccd2179c1c36576668a33caa4dc80d5"},"schema_version":"1.0","source":{"id":"2205.11164","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.11164","created_at":"2026-07-05T04:25:27Z"},{"alias_kind":"arxiv_version","alias_value":"2205.11164v1","created_at":"2026-07-05T04:25:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.11164","created_at":"2026-07-05T04:25:27Z"},{"alias_kind":"pith_short_12","alias_value":"L443YTVROE7D","created_at":"2026-07-05T04:25:27Z"},{"alias_kind":"pith_short_16","alias_value":"L443YTVROE7DOEN4","created_at":"2026-07-05T04:25:27Z"},{"alias_kind":"pith_short_8","alias_value":"L443YTVR","created_at":"2026-07-05T04:25:27Z"}],"graph_snapshots":[{"event_id":"sha256:f6bf90c6d36d93015bb1e71bdbc0f7f66d5f5f639e66a4af4022f32931309e74","target":"graph","created_at":"2026-07-05T04:25:27Z","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/2205.11164/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Many real-world tasks are plagued by limitations on data: in some instances very little data is available and in others, data is protected by privacy enforcing regulations (e.g. GDPR). We consider limitations posed specifically on time-series data and present a model that can generate synthetic time-series which can be used in place of real data. A model that generates synthetic time-series data has two objectives: 1) to capture the stepwise conditional distribution of real sequences, and 2) to faithfully model the joint distribution of entire real sequences. Autoregressive models trained via ","authors_text":"Padmanaba Srinivasan, William J. Knottenbelt","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2022-05-23T10:04:21Z","title":"Time-series Transformer Generative Adversarial Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.11164","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":"sha256:9d63f0ceaa637ea802971f2d3f6a2a3f6ef11b93e59e4b01f11d60b3a6766a97","target":"record","created_at":"2026-07-05T04:25:27Z","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":"ffd7d483e5f79d7baafc59ca0665a27dd4b81c4f36c543116178764c9a44f777","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2022-05-23T10:04:21Z","title_canon_sha256":"f4ea4f0fc91d6ed746843960893829727ccd2179c1c36576668a33caa4dc80d5"},"schema_version":"1.0","source":{"id":"2205.11164","kind":"arxiv","version":1}},"canonical_sha256":"5f39bc4eb1713e3711bc305afcc04238611c96f1922af6b1c0bb5bd9f61c5a3c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5f39bc4eb1713e3711bc305afcc04238611c96f1922af6b1c0bb5bd9f61c5a3c","first_computed_at":"2026-07-05T04:25:27.936056Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:25:27.936056Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fPW7tF5KAvqbnbSE5haOkbQOfyRBKWGzy97vUiK/AU1EYbQV5pIsXlwBAFuq3QWLf2dvtH1Gd1JK4DdSS/9QAg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:25:27.936428Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.11164","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9d63f0ceaa637ea802971f2d3f6a2a3f6ef11b93e59e4b01f11d60b3a6766a97","sha256:f6bf90c6d36d93015bb1e71bdbc0f7f66d5f5f639e66a4af4022f32931309e74"],"state_sha256":"4434db6c579f2ccfdaecb3d3146f78ab1efcd720a9cd9125ec7ea28e2f649122"}