{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:CJRRRFWW2SEHVWCEJI2WDOHDSF","short_pith_number":"pith:CJRRRFWW","canonical_record":{"source":{"id":"1808.05527","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-08-16T15:01:01Z","cross_cats_sorted":["cs.LG","q-fin.ST"],"title_canon_sha256":"1e272b78a8209d21592d482473b7ebb78814c12a7ef6d9a0236f11ace752989b","abstract_canon_sha256":"eaafabd0dea9a341fce9a3af7d4325ed95ef0023e3a80afd1fa9ce3aac4ed560"},"schema_version":"1.0"},"canonical_sha256":"12631896d6d4887ad8444a3561b8e3915a603d6bb85578167fef8a505561580f","source":{"kind":"arxiv","id":"1808.05527","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.05527","created_at":"2026-05-17T23:48:55Z"},{"alias_kind":"arxiv_version","alias_value":"1808.05527v3","created_at":"2026-05-17T23:48:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.05527","created_at":"2026-05-17T23:48:55Z"},{"alias_kind":"pith_short_12","alias_value":"CJRRRFWW2SEH","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"CJRRRFWW2SEHVWCE","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"CJRRRFWW","created_at":"2026-05-18T12:32:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:CJRRRFWW2SEHVWCEJI2WDOHDSF","target":"record","payload":{"canonical_record":{"source":{"id":"1808.05527","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-08-16T15:01:01Z","cross_cats_sorted":["cs.LG","q-fin.ST"],"title_canon_sha256":"1e272b78a8209d21592d482473b7ebb78814c12a7ef6d9a0236f11ace752989b","abstract_canon_sha256":"eaafabd0dea9a341fce9a3af7d4325ed95ef0023e3a80afd1fa9ce3aac4ed560"},"schema_version":"1.0"},"canonical_sha256":"12631896d6d4887ad8444a3561b8e3915a603d6bb85578167fef8a505561580f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:55.458996Z","signature_b64":"IECOJGkFtb19GWEgNS5DE7aCeCQPxgE0hIlcy/cYaYJj1Rz5+hnmGoBINDAwUZNuGdKt192ihmh3xVEc95eDBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"12631896d6d4887ad8444a3561b8e3915a603d6bb85578167fef8a505561580f","last_reissued_at":"2026-05-17T23:48:55.458494Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:55.458494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.05527","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:48:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SmgdYvnrapk8FmGLxKlAgGQWt51DBS1lYkGdRv5aRRQ5HKHsVXBkzRDmLxeJHTdsUDhNciQOvWToZvtHp5ELDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-23T14:31:52.089884Z"},"content_sha256":"8aa53242a52017463b34d7c086feac41f46d4064787a522f8ee7602b2ef252e9","schema_version":"1.0","event_id":"sha256:8aa53242a52017463b34d7c086feac41f46d4064787a522f8ee7602b2ef252e9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:CJRRRFWW2SEHVWCEJI2WDOHDSF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Learning for Energy Markets","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","q-fin.ST"],"primary_cat":"stat.ML","authors_text":"Michael Polson, Vadim Sokolov","submitted_at":"2018-08-16T15:01:01Z","abstract_excerpt":"Deep Learning is applied to energy markets to predict extreme loads observed in energy grids. Forecasting energy loads and prices is challenging due to sharp peaks and troughs that arise due to supply and demand fluctuations from intraday system constraints. We propose deep spatio-temporal models and extreme value theory (EVT) to capture theses effects and in particular the tail behavior of load spikes. Deep LSTM architectures with ReLU and $\\tanh$ activation functions can model trends and temporal dependencies while EVT captures highly volatile load spikes above a pre-specified threshold. To "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.05527","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-17T23:48:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IjPVj5WHbEFmLilDG5ukl5l3wi4gJvrme1V/kIMvkJlLdsIunTRYAm8LrjQVUZ+EzaMiNY5PjmGaqbFjjwpNDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-23T14:31:52.090229Z"},"content_sha256":"6d246d91b4fb45407c58915da38c0a96eadc1978fbba3f8ee8c2862914d7517e","schema_version":"1.0","event_id":"sha256:6d246d91b4fb45407c58915da38c0a96eadc1978fbba3f8ee8c2862914d7517e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CJRRRFWW2SEHVWCEJI2WDOHDSF/bundle.json","state_url":"https://pith.science/pith/CJRRRFWW2SEHVWCEJI2WDOHDSF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CJRRRFWW2SEHVWCEJI2WDOHDSF/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":"2026-06-23T14:31:52Z","links":{"resolver":"https://pith.science/pith/CJRRRFWW2SEHVWCEJI2WDOHDSF","bundle":"https://pith.science/pith/CJRRRFWW2SEHVWCEJI2WDOHDSF/bundle.json","state":"https://pith.science/pith/CJRRRFWW2SEHVWCEJI2WDOHDSF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CJRRRFWW2SEHVWCEJI2WDOHDSF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:CJRRRFWW2SEHVWCEJI2WDOHDSF","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":"eaafabd0dea9a341fce9a3af7d4325ed95ef0023e3a80afd1fa9ce3aac4ed560","cross_cats_sorted":["cs.LG","q-fin.ST"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-08-16T15:01:01Z","title_canon_sha256":"1e272b78a8209d21592d482473b7ebb78814c12a7ef6d9a0236f11ace752989b"},"schema_version":"1.0","source":{"id":"1808.05527","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.05527","created_at":"2026-05-17T23:48:55Z"},{"alias_kind":"arxiv_version","alias_value":"1808.05527v3","created_at":"2026-05-17T23:48:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.05527","created_at":"2026-05-17T23:48:55Z"},{"alias_kind":"pith_short_12","alias_value":"CJRRRFWW2SEH","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"CJRRRFWW2SEHVWCE","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"CJRRRFWW","created_at":"2026-05-18T12:32:16Z"}],"graph_snapshots":[{"event_id":"sha256:6d246d91b4fb45407c58915da38c0a96eadc1978fbba3f8ee8c2862914d7517e","target":"graph","created_at":"2026-05-17T23:48:55Z","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"},"paper":{"abstract_excerpt":"Deep Learning is applied to energy markets to predict extreme loads observed in energy grids. Forecasting energy loads and prices is challenging due to sharp peaks and troughs that arise due to supply and demand fluctuations from intraday system constraints. We propose deep spatio-temporal models and extreme value theory (EVT) to capture theses effects and in particular the tail behavior of load spikes. Deep LSTM architectures with ReLU and $\\tanh$ activation functions can model trends and temporal dependencies while EVT captures highly volatile load spikes above a pre-specified threshold. To ","authors_text":"Michael Polson, Vadim Sokolov","cross_cats":["cs.LG","q-fin.ST"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-08-16T15:01:01Z","title":"Deep Learning for Energy Markets"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.05527","kind":"arxiv","version":3},"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":"sha256:8aa53242a52017463b34d7c086feac41f46d4064787a522f8ee7602b2ef252e9","target":"record","created_at":"2026-05-17T23:48:55Z","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":"eaafabd0dea9a341fce9a3af7d4325ed95ef0023e3a80afd1fa9ce3aac4ed560","cross_cats_sorted":["cs.LG","q-fin.ST"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-08-16T15:01:01Z","title_canon_sha256":"1e272b78a8209d21592d482473b7ebb78814c12a7ef6d9a0236f11ace752989b"},"schema_version":"1.0","source":{"id":"1808.05527","kind":"arxiv","version":3}},"canonical_sha256":"12631896d6d4887ad8444a3561b8e3915a603d6bb85578167fef8a505561580f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"12631896d6d4887ad8444a3561b8e3915a603d6bb85578167fef8a505561580f","first_computed_at":"2026-05-17T23:48:55.458494Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:55.458494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IECOJGkFtb19GWEgNS5DE7aCeCQPxgE0hIlcy/cYaYJj1Rz5+hnmGoBINDAwUZNuGdKt192ihmh3xVEc95eDBw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:55.458996Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.05527","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8aa53242a52017463b34d7c086feac41f46d4064787a522f8ee7602b2ef252e9","sha256:6d246d91b4fb45407c58915da38c0a96eadc1978fbba3f8ee8c2862914d7517e"],"state_sha256":"9876eb78eeba18189a11bcafa7d4d9320a0e71fce1fcca470d9994d9cc8a9e30"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sxXcIEcCJcm/iVEY7T1wY9LyP5EV5rXvSrdNIsp9FvAyhuAAAZpg7bI20jJwfYDNzbUpt2YZSF+SGF8Guh0TCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-23T14:31:52.092403Z","bundle_sha256":"1ae333e183496d57ce06816be4afe13834c012dac3ac9ef05abbec0a8cc75a79"}}