{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:H3WA6FJPXMO4GN6HOJDVYYPBL2","short_pith_number":"pith:H3WA6FJP","canonical_record":{"source":{"id":"2104.05522","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-04-12T14:47:55Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"0be93265d336fdaa7219bd684d749eba388efe87bb98f0e7a1e8f6dcdf452c41","abstract_canon_sha256":"e43b9e27b4da3e958ca7278bf5c044a603c147cb3ce4cf66ba87ad6303fcdd69"},"schema_version":"1.0"},"canonical_sha256":"3eec0f152fbb1dc337c772475c61e15e88371a3062d7220dcc8b70b379b7f78e","source":{"kind":"arxiv","id":"2104.05522","version":6},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.05522","created_at":"2026-07-05T04:47:07Z"},{"alias_kind":"arxiv_version","alias_value":"2104.05522v6","created_at":"2026-07-05T04:47:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.05522","created_at":"2026-07-05T04:47:07Z"},{"alias_kind":"pith_short_12","alias_value":"H3WA6FJPXMO4","created_at":"2026-07-05T04:47:07Z"},{"alias_kind":"pith_short_16","alias_value":"H3WA6FJPXMO4GN6H","created_at":"2026-07-05T04:47:07Z"},{"alias_kind":"pith_short_8","alias_value":"H3WA6FJP","created_at":"2026-07-05T04:47:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:H3WA6FJPXMO4GN6HOJDVYYPBL2","target":"record","payload":{"canonical_record":{"source":{"id":"2104.05522","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-04-12T14:47:55Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"0be93265d336fdaa7219bd684d749eba388efe87bb98f0e7a1e8f6dcdf452c41","abstract_canon_sha256":"e43b9e27b4da3e958ca7278bf5c044a603c147cb3ce4cf66ba87ad6303fcdd69"},"schema_version":"1.0"},"canonical_sha256":"3eec0f152fbb1dc337c772475c61e15e88371a3062d7220dcc8b70b379b7f78e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:47:07.536783Z","signature_b64":"BapEDe2D00CmmFYRKsT3GB8z2Bqd4TCM41lehHFJdEZsjk9E+8b76gGSi6BMhVprhzkTabt65HmNbhrB7Hc1Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3eec0f152fbb1dc337c772475c61e15e88371a3062d7220dcc8b70b379b7f78e","last_reissued_at":"2026-07-05T04:47:07.536307Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:47:07.536307Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.05522","source_version":6,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:47:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"91g4NTXBI0aK9GQqoBGvT5k5PzJS+P+oQnkT/ms7eouoXliCpyebKAWt54pWiZmxlCMWwnLz3dQ9DS3bl5BhAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T19:46:58.790998Z"},"content_sha256":"e0bd665b57cb35acb2d6e1edafdfcd9c56e8388983bdf11e2e91835bfc936982","schema_version":"1.0","event_id":"sha256:e0bd665b57cb35acb2d6e1edafdfcd9c56e8388983bdf11e2e91835bfc936982"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:H3WA6FJPXMO4GN6HOJDVYYPBL2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Artur Dubrawski, Cristian Challu, Grzegorz Marcjasz, Kin G. Olivares, Rafa{\\l} Weron","submitted_at":"2021-04-12T14:47:55Z","abstract_excerpt":"We extend the neural basis expansion analysis (NBEATS) to incorporate exogenous factors. The resulting method, called NBEATSx, improves on a well performing deep learning model, extending its capabilities by including exogenous variables and allowing it to integrate multiple sources of useful information. To showcase the utility of the NBEATSx model, we conduct a comprehensive study of its application to electricity price forecasting (EPF) tasks across a broad range of years and markets. We observe state-of-the-art performance, significantly improving the forecast accuracy by nearly 20% over t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.05522","kind":"arxiv","version":6},"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/2104.05522/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":"2026-07-05T04:47:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p9ThCMAswQ6O2HM24sN1bUbi8FJLnOx75+30kU13RRvqMLCNz6xt0wJvuu0TTVMMUcezvZ0E8TJ4mtBXCjmSAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T19:46:58.791311Z"},"content_sha256":"9d678a1e0948d584291bc55e798b1c19c46c4a68f9c540b8fe2119229126d545","schema_version":"1.0","event_id":"sha256:9d678a1e0948d584291bc55e798b1c19c46c4a68f9c540b8fe2119229126d545"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/H3WA6FJPXMO4GN6HOJDVYYPBL2/bundle.json","state_url":"https://pith.science/pith/H3WA6FJPXMO4GN6HOJDVYYPBL2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/H3WA6FJPXMO4GN6HOJDVYYPBL2/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":"2026-07-31T19:46:58Z","links":{"resolver":"https://pith.science/pith/H3WA6FJPXMO4GN6HOJDVYYPBL2","bundle":"https://pith.science/pith/H3WA6FJPXMO4GN6HOJDVYYPBL2/bundle.json","state":"https://pith.science/pith/H3WA6FJPXMO4GN6HOJDVYYPBL2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/H3WA6FJPXMO4GN6HOJDVYYPBL2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:H3WA6FJPXMO4GN6HOJDVYYPBL2","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":"e43b9e27b4da3e958ca7278bf5c044a603c147cb3ce4cf66ba87ad6303fcdd69","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-04-12T14:47:55Z","title_canon_sha256":"0be93265d336fdaa7219bd684d749eba388efe87bb98f0e7a1e8f6dcdf452c41"},"schema_version":"1.0","source":{"id":"2104.05522","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.05522","created_at":"2026-07-05T04:47:07Z"},{"alias_kind":"arxiv_version","alias_value":"2104.05522v6","created_at":"2026-07-05T04:47:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.05522","created_at":"2026-07-05T04:47:07Z"},{"alias_kind":"pith_short_12","alias_value":"H3WA6FJPXMO4","created_at":"2026-07-05T04:47:07Z"},{"alias_kind":"pith_short_16","alias_value":"H3WA6FJPXMO4GN6H","created_at":"2026-07-05T04:47:07Z"},{"alias_kind":"pith_short_8","alias_value":"H3WA6FJP","created_at":"2026-07-05T04:47:07Z"}],"graph_snapshots":[{"event_id":"sha256:9d678a1e0948d584291bc55e798b1c19c46c4a68f9c540b8fe2119229126d545","target":"graph","created_at":"2026-07-05T04:47:07Z","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/2104.05522/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We extend the neural basis expansion analysis (NBEATS) to incorporate exogenous factors. The resulting method, called NBEATSx, improves on a well performing deep learning model, extending its capabilities by including exogenous variables and allowing it to integrate multiple sources of useful information. To showcase the utility of the NBEATSx model, we conduct a comprehensive study of its application to electricity price forecasting (EPF) tasks across a broad range of years and markets. We observe state-of-the-art performance, significantly improving the forecast accuracy by nearly 20% over t","authors_text":"Artur Dubrawski, Cristian Challu, Grzegorz Marcjasz, Kin G. Olivares, Rafa{\\l} Weron","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-04-12T14:47:55Z","title":"Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.05522","kind":"arxiv","version":6},"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:e0bd665b57cb35acb2d6e1edafdfcd9c56e8388983bdf11e2e91835bfc936982","target":"record","created_at":"2026-07-05T04:47:07Z","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":"e43b9e27b4da3e958ca7278bf5c044a603c147cb3ce4cf66ba87ad6303fcdd69","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-04-12T14:47:55Z","title_canon_sha256":"0be93265d336fdaa7219bd684d749eba388efe87bb98f0e7a1e8f6dcdf452c41"},"schema_version":"1.0","source":{"id":"2104.05522","kind":"arxiv","version":6}},"canonical_sha256":"3eec0f152fbb1dc337c772475c61e15e88371a3062d7220dcc8b70b379b7f78e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3eec0f152fbb1dc337c772475c61e15e88371a3062d7220dcc8b70b379b7f78e","first_computed_at":"2026-07-05T04:47:07.536307Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:47:07.536307Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BapEDe2D00CmmFYRKsT3GB8z2Bqd4TCM41lehHFJdEZsjk9E+8b76gGSi6BMhVprhzkTabt65HmNbhrB7Hc1Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:47:07.536783Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.05522","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e0bd665b57cb35acb2d6e1edafdfcd9c56e8388983bdf11e2e91835bfc936982","sha256:9d678a1e0948d584291bc55e798b1c19c46c4a68f9c540b8fe2119229126d545"],"state_sha256":"da8b44fbea8aa7c296e98a2fc3859ae45d13a24ac2245b0001302e00e0b5c8f8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e0SLagqnMBgGW04dSl5pqusg9N8tt+EU+C/FDDVxuS7pbpjZiIwsj36EU1hiHMAt2prLN/pgFO8KpjjKGxi1CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T19:46:58.794225Z","bundle_sha256":"1ba4bc301ab965a561abb1bc446beff26e151c7aef16c0dd3f69d9a79f676ca6"}}