{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:LFAJD22QLF2IAL2HZG7OIP2ODP","short_pith_number":"pith:LFAJD22Q","canonical_record":{"source":{"id":"2103.12969","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-03-24T03:47:20Z","cross_cats_sorted":["eess.SP"],"title_canon_sha256":"72174fa55e630ee654c3b6f2fea12cc9a38bab758aaaf92703fd11f385621547","abstract_canon_sha256":"a5b445c7f5cc714638fb00ad605fdf03f66de3cb3b9daed0860c55f82930dab3"},"schema_version":"1.0"},"canonical_sha256":"594091eb505974802f47c9bee43f4e1bd4410c99760c966ad33d63730266b1c0","source":{"kind":"arxiv","id":"2103.12969","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.12969","created_at":"2026-07-05T05:36:44Z"},{"alias_kind":"arxiv_version","alias_value":"2103.12969v2","created_at":"2026-07-05T05:36:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.12969","created_at":"2026-07-05T05:36:44Z"},{"alias_kind":"pith_short_12","alias_value":"LFAJD22QLF2I","created_at":"2026-07-05T05:36:44Z"},{"alias_kind":"pith_short_16","alias_value":"LFAJD22QLF2IAL2H","created_at":"2026-07-05T05:36:44Z"},{"alias_kind":"pith_short_8","alias_value":"LFAJD22Q","created_at":"2026-07-05T05:36:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:LFAJD22QLF2IAL2HZG7OIP2ODP","target":"record","payload":{"canonical_record":{"source":{"id":"2103.12969","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-03-24T03:47:20Z","cross_cats_sorted":["eess.SP"],"title_canon_sha256":"72174fa55e630ee654c3b6f2fea12cc9a38bab758aaaf92703fd11f385621547","abstract_canon_sha256":"a5b445c7f5cc714638fb00ad605fdf03f66de3cb3b9daed0860c55f82930dab3"},"schema_version":"1.0"},"canonical_sha256":"594091eb505974802f47c9bee43f4e1bd4410c99760c966ad33d63730266b1c0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:36:44.181951Z","signature_b64":"geox1UGwaZ4qtmE2y+4IE9q/aIAjr6Ac8uQDVvzxrEGV2oQpc9s57tmkFSbI5Vff05XinK9ZVUAZ8CBr9OvmAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"594091eb505974802f47c9bee43f4e1bd4410c99760c966ad33d63730266b1c0","last_reissued_at":"2026-07-05T05:36:44.181457Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:36:44.181457Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2103.12969","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":"2026-07-05T05:36:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6iTZoBevLBfn60YP+SAWEnE+UzAQ+JarU9l1vPDhIWX08cbzA43RipdwU0bYJDs/LuBIEBWzmXGUVcckol2/Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T16:24:13.899999Z"},"content_sha256":"c5f3b384da83bef0686cf28f8fa6183dcf7fa4fc9ad929750e314619a4012628","schema_version":"1.0","event_id":"sha256:c5f3b384da83bef0686cf28f8fa6183dcf7fa4fc9ad929750e314619a4012628"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:LFAJD22QLF2IAL2HZG7OIP2ODP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A VAE-Bayesian Deep Learning Scheme for Solar Generation Forecasting based on Dimensionality Reduction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["eess.SP"],"primary_cat":"cs.LG","authors_text":"Adnan Anwar, Devinder Kaur, Md. Apel Mahmud, Md. Enamul Haque, Shama Naz Islam","submitted_at":"2021-03-24T03:47:20Z","abstract_excerpt":"The advancement of distributed generation technologies in modern power systems has led to a widespread integration of renewable power generation at customer side. However, the intermittent nature of renewable energy poses new challenges to the network operational planning with underlying uncertainties. This paper proposes a novel Bayesian probabilistic technique for forecasting renewable solar generation by addressing data and model uncertainties by integrating bidirectional long short-term memory (BiLSTM) neural networks while compressing the weight parameters using variational autoencoder (V"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.12969","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/2103.12969/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":"2026-07-05T05:36:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2FmQes2iF5xAXYnUjWDSo3XYNCRhQ0RlQUY9v1L3K7ET0tu9LTAq/ddE2wGkmJUgXk186iSGcoemhcGNViOKDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T16:24:13.900398Z"},"content_sha256":"78b4a6937f9b45e0d03028e30f1797b8be2d2ac413fed8d05cfdd34df415fe5e","schema_version":"1.0","event_id":"sha256:78b4a6937f9b45e0d03028e30f1797b8be2d2ac413fed8d05cfdd34df415fe5e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LFAJD22QLF2IAL2HZG7OIP2ODP/bundle.json","state_url":"https://pith.science/pith/LFAJD22QLF2IAL2HZG7OIP2ODP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LFAJD22QLF2IAL2HZG7OIP2ODP/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":"2026-07-08T16:24:13Z","links":{"resolver":"https://pith.science/pith/LFAJD22QLF2IAL2HZG7OIP2ODP","bundle":"https://pith.science/pith/LFAJD22QLF2IAL2HZG7OIP2ODP/bundle.json","state":"https://pith.science/pith/LFAJD22QLF2IAL2HZG7OIP2ODP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LFAJD22QLF2IAL2HZG7OIP2ODP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:LFAJD22QLF2IAL2HZG7OIP2ODP","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":"a5b445c7f5cc714638fb00ad605fdf03f66de3cb3b9daed0860c55f82930dab3","cross_cats_sorted":["eess.SP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-03-24T03:47:20Z","title_canon_sha256":"72174fa55e630ee654c3b6f2fea12cc9a38bab758aaaf92703fd11f385621547"},"schema_version":"1.0","source":{"id":"2103.12969","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.12969","created_at":"2026-07-05T05:36:44Z"},{"alias_kind":"arxiv_version","alias_value":"2103.12969v2","created_at":"2026-07-05T05:36:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.12969","created_at":"2026-07-05T05:36:44Z"},{"alias_kind":"pith_short_12","alias_value":"LFAJD22QLF2I","created_at":"2026-07-05T05:36:44Z"},{"alias_kind":"pith_short_16","alias_value":"LFAJD22QLF2IAL2H","created_at":"2026-07-05T05:36:44Z"},{"alias_kind":"pith_short_8","alias_value":"LFAJD22Q","created_at":"2026-07-05T05:36:44Z"}],"graph_snapshots":[{"event_id":"sha256:78b4a6937f9b45e0d03028e30f1797b8be2d2ac413fed8d05cfdd34df415fe5e","target":"graph","created_at":"2026-07-05T05:36:44Z","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/2103.12969/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The advancement of distributed generation technologies in modern power systems has led to a widespread integration of renewable power generation at customer side. However, the intermittent nature of renewable energy poses new challenges to the network operational planning with underlying uncertainties. This paper proposes a novel Bayesian probabilistic technique for forecasting renewable solar generation by addressing data and model uncertainties by integrating bidirectional long short-term memory (BiLSTM) neural networks while compressing the weight parameters using variational autoencoder (V","authors_text":"Adnan Anwar, Devinder Kaur, Md. Apel Mahmud, Md. Enamul Haque, Shama Naz Islam","cross_cats":["eess.SP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-03-24T03:47:20Z","title":"A VAE-Bayesian Deep Learning Scheme for Solar Generation Forecasting based on Dimensionality Reduction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.12969","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:c5f3b384da83bef0686cf28f8fa6183dcf7fa4fc9ad929750e314619a4012628","target":"record","created_at":"2026-07-05T05:36:44Z","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":"a5b445c7f5cc714638fb00ad605fdf03f66de3cb3b9daed0860c55f82930dab3","cross_cats_sorted":["eess.SP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-03-24T03:47:20Z","title_canon_sha256":"72174fa55e630ee654c3b6f2fea12cc9a38bab758aaaf92703fd11f385621547"},"schema_version":"1.0","source":{"id":"2103.12969","kind":"arxiv","version":2}},"canonical_sha256":"594091eb505974802f47c9bee43f4e1bd4410c99760c966ad33d63730266b1c0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"594091eb505974802f47c9bee43f4e1bd4410c99760c966ad33d63730266b1c0","first_computed_at":"2026-07-05T05:36:44.181457Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:36:44.181457Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"geox1UGwaZ4qtmE2y+4IE9q/aIAjr6Ac8uQDVvzxrEGV2oQpc9s57tmkFSbI5Vff05XinK9ZVUAZ8CBr9OvmAA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:36:44.181951Z","signed_message":"canonical_sha256_bytes"},"source_id":"2103.12969","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c5f3b384da83bef0686cf28f8fa6183dcf7fa4fc9ad929750e314619a4012628","sha256:78b4a6937f9b45e0d03028e30f1797b8be2d2ac413fed8d05cfdd34df415fe5e"],"state_sha256":"855d34a91b949b66f6aae0e12ff39c99b1ed5c443ae87d265dff265113af4d12"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uD8fgYdwPlSx4IBqQv8yyRRM4I+FmBXbywx2uFEn/Jlw5+wIPipEM8toaEULwjrHmJA4o2z7rtDUEikMzMLKAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T16:24:13.902621Z","bundle_sha256":"4494e84f98a9e041cc3e99a9827db37096d956f4afab15ece25cfcc6cc854efd"}}