{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:W7CJMLABC3KU62ZN2U7UNSLDDL","short_pith_number":"pith:W7CJMLAB","canonical_record":{"source":{"id":"2202.11316","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-02-23T05:22:03Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"239efb46071a5ba33724fc2c2085d2d06744132b5969232764fd8e233455ba4a","abstract_canon_sha256":"694d5eeecb99eff302a079677d5b24535ab48041264f4f4e1b3ed1feeeb608f7"},"schema_version":"1.0"},"canonical_sha256":"b7c4962c0116d54f6b2dd53f46c9631af728625a3a758f7a056e8c61e049e7f7","source":{"kind":"arxiv","id":"2202.11316","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.11316","created_at":"2026-07-05T05:22:06Z"},{"alias_kind":"arxiv_version","alias_value":"2202.11316v2","created_at":"2026-07-05T05:22:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.11316","created_at":"2026-07-05T05:22:06Z"},{"alias_kind":"pith_short_12","alias_value":"W7CJMLABC3KU","created_at":"2026-07-05T05:22:06Z"},{"alias_kind":"pith_short_16","alias_value":"W7CJMLABC3KU62ZN","created_at":"2026-07-05T05:22:06Z"},{"alias_kind":"pith_short_8","alias_value":"W7CJMLAB","created_at":"2026-07-05T05:22:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:W7CJMLABC3KU62ZN2U7UNSLDDL","target":"record","payload":{"canonical_record":{"source":{"id":"2202.11316","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-02-23T05:22:03Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"239efb46071a5ba33724fc2c2085d2d06744132b5969232764fd8e233455ba4a","abstract_canon_sha256":"694d5eeecb99eff302a079677d5b24535ab48041264f4f4e1b3ed1feeeb608f7"},"schema_version":"1.0"},"canonical_sha256":"b7c4962c0116d54f6b2dd53f46c9631af728625a3a758f7a056e8c61e049e7f7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:22:06.268219Z","signature_b64":"ZhhWkb6+raJ53DdW1ZNDLC6jYXrF2fzX5BfwkcW0XAqQKZIt9I6erD/1g9s/c7Y2Kf9+zC8C3yXaw6oawSYGAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b7c4962c0116d54f6b2dd53f46c9631af728625a3a758f7a056e8c61e049e7f7","last_reissued_at":"2026-07-05T05:22:06.267801Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:22:06.267801Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2202.11316","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":"2026-07-05T05:22:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l2x5wTBM9GSZ7EMlW8whTQyJqDKy2z9GCirpWS+ZZZeUqk85UQyhD+/Nje4N/KxCijc8hqcExKgHvz44BRmCDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T09:40:39.611577Z"},"content_sha256":"a3d5c43cadf303896d9603cd2787a7860298834c93cd731b00c9e9d162b82318","schema_version":"1.0","event_id":"sha256:a3d5c43cadf303896d9603cd2787a7860298834c93cd731b00c9e9d162b82318"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:W7CJMLABC3KU62ZN2U7UNSLDDL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multivariate Quantile Function Forecaster","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Fran\\c{c}ois-Xavier Aubet, Jan Gasthaus, Kelvin Kan, Konstantinos Benidis, Lars Ruthotto, Tim januschowski, Youngsuk Park","submitted_at":"2022-02-23T05:22:03Z","abstract_excerpt":"We propose Multivariate Quantile Function Forecaster (MQF$^2$), a global probabilistic forecasting method constructed using a multivariate quantile function and investigate its application to multi-horizon forecasting. Prior approaches are either autoregressive, implicitly capturing the dependency structure across time but exhibiting error accumulation with increasing forecast horizons, or multi-horizon sequence-to-sequence models, which do not exhibit error accumulation, but also do typically not model the dependency structure across time steps. MQF$^2$ combines the benefits of both approache"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.11316","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/2202.11316/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":"2026-07-05T05:22:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9X9vr+XktM89DZSm75Jf76cpHLqaWSGL8nPuieVEaBF2zGv1to6YmiyZVNxdm/3sYTGMX6VI6ZAiZRERqCxiCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T09:40:39.611950Z"},"content_sha256":"9ab0a4de9be5c4d53f77d7ff42c939ac6f234762befb78218fab916b19df47a7","schema_version":"1.0","event_id":"sha256:9ab0a4de9be5c4d53f77d7ff42c939ac6f234762befb78218fab916b19df47a7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W7CJMLABC3KU62ZN2U7UNSLDDL/bundle.json","state_url":"https://pith.science/pith/W7CJMLABC3KU62ZN2U7UNSLDDL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W7CJMLABC3KU62ZN2U7UNSLDDL/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":"2026-07-12T09:40:39Z","links":{"resolver":"https://pith.science/pith/W7CJMLABC3KU62ZN2U7UNSLDDL","bundle":"https://pith.science/pith/W7CJMLABC3KU62ZN2U7UNSLDDL/bundle.json","state":"https://pith.science/pith/W7CJMLABC3KU62ZN2U7UNSLDDL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W7CJMLABC3KU62ZN2U7UNSLDDL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:W7CJMLABC3KU62ZN2U7UNSLDDL","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":"694d5eeecb99eff302a079677d5b24535ab48041264f4f4e1b3ed1feeeb608f7","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-02-23T05:22:03Z","title_canon_sha256":"239efb46071a5ba33724fc2c2085d2d06744132b5969232764fd8e233455ba4a"},"schema_version":"1.0","source":{"id":"2202.11316","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.11316","created_at":"2026-07-05T05:22:06Z"},{"alias_kind":"arxiv_version","alias_value":"2202.11316v2","created_at":"2026-07-05T05:22:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.11316","created_at":"2026-07-05T05:22:06Z"},{"alias_kind":"pith_short_12","alias_value":"W7CJMLABC3KU","created_at":"2026-07-05T05:22:06Z"},{"alias_kind":"pith_short_16","alias_value":"W7CJMLABC3KU62ZN","created_at":"2026-07-05T05:22:06Z"},{"alias_kind":"pith_short_8","alias_value":"W7CJMLAB","created_at":"2026-07-05T05:22:06Z"}],"graph_snapshots":[{"event_id":"sha256:9ab0a4de9be5c4d53f77d7ff42c939ac6f234762befb78218fab916b19df47a7","target":"graph","created_at":"2026-07-05T05:22:06Z","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/2202.11316/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose Multivariate Quantile Function Forecaster (MQF$^2$), a global probabilistic forecasting method constructed using a multivariate quantile function and investigate its application to multi-horizon forecasting. Prior approaches are either autoregressive, implicitly capturing the dependency structure across time but exhibiting error accumulation with increasing forecast horizons, or multi-horizon sequence-to-sequence models, which do not exhibit error accumulation, but also do typically not model the dependency structure across time steps. MQF$^2$ combines the benefits of both approache","authors_text":"Fran\\c{c}ois-Xavier Aubet, Jan Gasthaus, Kelvin Kan, Konstantinos Benidis, Lars Ruthotto, Tim januschowski, Youngsuk Park","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-02-23T05:22:03Z","title":"Multivariate Quantile Function Forecaster"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.11316","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:a3d5c43cadf303896d9603cd2787a7860298834c93cd731b00c9e9d162b82318","target":"record","created_at":"2026-07-05T05:22:06Z","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":"694d5eeecb99eff302a079677d5b24535ab48041264f4f4e1b3ed1feeeb608f7","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-02-23T05:22:03Z","title_canon_sha256":"239efb46071a5ba33724fc2c2085d2d06744132b5969232764fd8e233455ba4a"},"schema_version":"1.0","source":{"id":"2202.11316","kind":"arxiv","version":2}},"canonical_sha256":"b7c4962c0116d54f6b2dd53f46c9631af728625a3a758f7a056e8c61e049e7f7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b7c4962c0116d54f6b2dd53f46c9631af728625a3a758f7a056e8c61e049e7f7","first_computed_at":"2026-07-05T05:22:06.267801Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:22:06.267801Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZhhWkb6+raJ53DdW1ZNDLC6jYXrF2fzX5BfwkcW0XAqQKZIt9I6erD/1g9s/c7Y2Kf9+zC8C3yXaw6oawSYGAg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:22:06.268219Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.11316","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a3d5c43cadf303896d9603cd2787a7860298834c93cd731b00c9e9d162b82318","sha256:9ab0a4de9be5c4d53f77d7ff42c939ac6f234762befb78218fab916b19df47a7"],"state_sha256":"0e94b89712a3fbf5ba1338f65b63b22b667f89b1395430e2f555a70b2279ee1d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pNAr5HUZjvMiK80HwBDWAWcJ92+QpUI6ex+FwDdaDdVV7fFL3w+xk91CB/WrBSJNba5Tm102OQfpLae6KMxKAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-12T09:40:39.614366Z","bundle_sha256":"0a30e699633c894a9c38f3e0c7fb086e0aed0b154aeeb399f9915f829f3c61f5"}}