{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:QEN6R37UUFTKBJE3GOBSDLXOHK","short_pith_number":"pith:QEN6R37U","canonical_record":{"source":{"id":"2110.02166","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2021-10-01T19:18:13Z","cross_cats_sorted":["cs.LG","stat.AP"],"title_canon_sha256":"2116b2811adf2ae78b0ba5c5b4a932e0580471abd3a019632b3324d57c49a2df","abstract_canon_sha256":"6f702dc69ee40334fcbed33fe6f309e8ffbde8cb3e27d96c94789abd7848ff68"},"schema_version":"1.0"},"canonical_sha256":"811be8eff4a166a0a49b338321aeee3ab033750ab17b8ad45f787757ffb8349b","source":{"kind":"arxiv","id":"2110.02166","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.02166","created_at":"2026-07-05T03:20:16Z"},{"alias_kind":"arxiv_version","alias_value":"2110.02166v1","created_at":"2026-07-05T03:20:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.02166","created_at":"2026-07-05T03:20:16Z"},{"alias_kind":"pith_short_12","alias_value":"QEN6R37UUFTK","created_at":"2026-07-05T03:20:16Z"},{"alias_kind":"pith_short_16","alias_value":"QEN6R37UUFTKBJE3","created_at":"2026-07-05T03:20:16Z"},{"alias_kind":"pith_short_8","alias_value":"QEN6R37U","created_at":"2026-07-05T03:20:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:QEN6R37UUFTKBJE3GOBSDLXOHK","target":"record","payload":{"canonical_record":{"source":{"id":"2110.02166","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2021-10-01T19:18:13Z","cross_cats_sorted":["cs.LG","stat.AP"],"title_canon_sha256":"2116b2811adf2ae78b0ba5c5b4a932e0580471abd3a019632b3324d57c49a2df","abstract_canon_sha256":"6f702dc69ee40334fcbed33fe6f309e8ffbde8cb3e27d96c94789abd7848ff68"},"schema_version":"1.0"},"canonical_sha256":"811be8eff4a166a0a49b338321aeee3ab033750ab17b8ad45f787757ffb8349b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:20:16.475885Z","signature_b64":"fTsjjUrbXKpzqtMYsj0kpOmnIGQVGmrwysDVJZ797hhmZyP+IL6wHit75TDpLCRhkSfjXsXGIqWe8ZIEGGAwAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"811be8eff4a166a0a49b338321aeee3ab033750ab17b8ad45f787757ffb8349b","last_reissued_at":"2026-07-05T03:20:16.475542Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:20:16.475542Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.02166","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":"2026-07-05T03:20:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"o4TkRMO4oc0GCfcLXGYz57Cj84LE6ikJCy0fjFpAwQCKPSgVW7mp6AGyrwfv4srAuCdRsgR0o0KTlNkmIDyqAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:45:42.724986Z"},"content_sha256":"f92c0cf5c285cb9d0dd08c96ef9feb9364a3f253c6583988e8ddc63b11666bae","schema_version":"1.0","event_id":"sha256:f92c0cf5c285cb9d0dd08c96ef9feb9364a3f253c6583988e8ddc63b11666bae"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:QEN6R37UUFTKBJE3GOBSDLXOHK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Prediction of Energy Consumption for Variable Customer Portfolios Including Aleatoric Uncertainty Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.AP"],"primary_cat":"eess.SP","authors_text":"Andr\\'e Schneider, Olaf Enge-Rosenblatt, Oliver Mey, Pit Stenzel, Yesnier Bravo","submitted_at":"2021-10-01T19:18:13Z","abstract_excerpt":"Using hourly energy consumption data recorded by smart meters, retailers can estimate the day-ahead energy consumption of their customer portfolio. Deep neural networks are especially suited for this task as a huge amount of historical consumption data is available from smart meter recordings to be used for model training. Probabilistic layers further enable the estimation of the uncertainty of the consumption forecasts. Here, we propose a method to calculate hourly day-ahead energy consumption forecasts which include an estimation of the aleatoric uncertainty. To consider the statistical prop"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.02166","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/2110.02166/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":"2026-07-05T03:20:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QUClmzbhSBw/x6aqx8EVlXXHInkGZjNvvlsxy+ewOh2/qE9NxuM2sFVFuI4tunxe9kiSiL0H9uDpeiD3o32uCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:45:42.725370Z"},"content_sha256":"2838db9dd3119602a6262c51b1772d242a5a6b92ccd16261886f60435d963a6b","schema_version":"1.0","event_id":"sha256:2838db9dd3119602a6262c51b1772d242a5a6b92ccd16261886f60435d963a6b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QEN6R37UUFTKBJE3GOBSDLXOHK/bundle.json","state_url":"https://pith.science/pith/QEN6R37UUFTKBJE3GOBSDLXOHK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QEN6R37UUFTKBJE3GOBSDLXOHK/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":"2026-07-06T18:45:42Z","links":{"resolver":"https://pith.science/pith/QEN6R37UUFTKBJE3GOBSDLXOHK","bundle":"https://pith.science/pith/QEN6R37UUFTKBJE3GOBSDLXOHK/bundle.json","state":"https://pith.science/pith/QEN6R37UUFTKBJE3GOBSDLXOHK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QEN6R37UUFTKBJE3GOBSDLXOHK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:QEN6R37UUFTKBJE3GOBSDLXOHK","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":"6f702dc69ee40334fcbed33fe6f309e8ffbde8cb3e27d96c94789abd7848ff68","cross_cats_sorted":["cs.LG","stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2021-10-01T19:18:13Z","title_canon_sha256":"2116b2811adf2ae78b0ba5c5b4a932e0580471abd3a019632b3324d57c49a2df"},"schema_version":"1.0","source":{"id":"2110.02166","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.02166","created_at":"2026-07-05T03:20:16Z"},{"alias_kind":"arxiv_version","alias_value":"2110.02166v1","created_at":"2026-07-05T03:20:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.02166","created_at":"2026-07-05T03:20:16Z"},{"alias_kind":"pith_short_12","alias_value":"QEN6R37UUFTK","created_at":"2026-07-05T03:20:16Z"},{"alias_kind":"pith_short_16","alias_value":"QEN6R37UUFTKBJE3","created_at":"2026-07-05T03:20:16Z"},{"alias_kind":"pith_short_8","alias_value":"QEN6R37U","created_at":"2026-07-05T03:20:16Z"}],"graph_snapshots":[{"event_id":"sha256:2838db9dd3119602a6262c51b1772d242a5a6b92ccd16261886f60435d963a6b","target":"graph","created_at":"2026-07-05T03:20:16Z","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/2110.02166/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Using hourly energy consumption data recorded by smart meters, retailers can estimate the day-ahead energy consumption of their customer portfolio. Deep neural networks are especially suited for this task as a huge amount of historical consumption data is available from smart meter recordings to be used for model training. Probabilistic layers further enable the estimation of the uncertainty of the consumption forecasts. Here, we propose a method to calculate hourly day-ahead energy consumption forecasts which include an estimation of the aleatoric uncertainty. To consider the statistical prop","authors_text":"Andr\\'e Schneider, Olaf Enge-Rosenblatt, Oliver Mey, Pit Stenzel, Yesnier Bravo","cross_cats":["cs.LG","stat.AP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2021-10-01T19:18:13Z","title":"Prediction of Energy Consumption for Variable Customer Portfolios Including Aleatoric Uncertainty Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.02166","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:f92c0cf5c285cb9d0dd08c96ef9feb9364a3f253c6583988e8ddc63b11666bae","target":"record","created_at":"2026-07-05T03:20:16Z","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":"6f702dc69ee40334fcbed33fe6f309e8ffbde8cb3e27d96c94789abd7848ff68","cross_cats_sorted":["cs.LG","stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2021-10-01T19:18:13Z","title_canon_sha256":"2116b2811adf2ae78b0ba5c5b4a932e0580471abd3a019632b3324d57c49a2df"},"schema_version":"1.0","source":{"id":"2110.02166","kind":"arxiv","version":1}},"canonical_sha256":"811be8eff4a166a0a49b338321aeee3ab033750ab17b8ad45f787757ffb8349b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"811be8eff4a166a0a49b338321aeee3ab033750ab17b8ad45f787757ffb8349b","first_computed_at":"2026-07-05T03:20:16.475542Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:20:16.475542Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fTsjjUrbXKpzqtMYsj0kpOmnIGQVGmrwysDVJZ797hhmZyP+IL6wHit75TDpLCRhkSfjXsXGIqWe8ZIEGGAwAg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:20:16.475885Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.02166","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f92c0cf5c285cb9d0dd08c96ef9feb9364a3f253c6583988e8ddc63b11666bae","sha256:2838db9dd3119602a6262c51b1772d242a5a6b92ccd16261886f60435d963a6b"],"state_sha256":"6828a879653576d7519b082f2a3c3ab8bcb66321abd087ce735c9af5bb843da8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1Up3XFV6/VrZRRnb22B8xdU7nCdMEw8M8WF6skkLwIOmwa4CeiY0RH0KAcq9sN4qaANUSMn3wOEVU29DFSKaBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T18:45:42.727310Z","bundle_sha256":"5b76b6f5247ce3a9a05c75948481305c3732e885374d22d70431dfd5c43f9714"}}