{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:FIG6M3FNTXI2T73MW6AO5NQ5GB","short_pith_number":"pith:FIG6M3FN","canonical_record":{"source":{"id":"1801.09870","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-01-30T07:10:36Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"03f400b07cd438c69b6ac4b48ee221ba796081d990c472cf495f2dd1e07a6dba","abstract_canon_sha256":"32e6c07f3c98ce4a1cfe6f3bb7e9f67ca91d7ca0cfdfd5722131934967c04906"},"schema_version":"1.0"},"canonical_sha256":"2a0de66cad9dd1a9ff6cb780eeb61d3053ab66ce03ff1ae7023505e3cc72bed5","source":{"kind":"arxiv","id":"1801.09870","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.09870","created_at":"2026-05-18T00:24:46Z"},{"alias_kind":"arxiv_version","alias_value":"1801.09870v1","created_at":"2026-05-18T00:24:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.09870","created_at":"2026-05-18T00:24:46Z"},{"alias_kind":"pith_short_12","alias_value":"FIG6M3FNTXI2","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"FIG6M3FNTXI2T73M","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"FIG6M3FN","created_at":"2026-05-18T12:32:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:FIG6M3FNTXI2T73MW6AO5NQ5GB","target":"record","payload":{"canonical_record":{"source":{"id":"1801.09870","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-01-30T07:10:36Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"03f400b07cd438c69b6ac4b48ee221ba796081d990c472cf495f2dd1e07a6dba","abstract_canon_sha256":"32e6c07f3c98ce4a1cfe6f3bb7e9f67ca91d7ca0cfdfd5722131934967c04906"},"schema_version":"1.0"},"canonical_sha256":"2a0de66cad9dd1a9ff6cb780eeb61d3053ab66ce03ff1ae7023505e3cc72bed5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:24:46.537708Z","signature_b64":"8eKnBDRN695oYBXHHtKIMiucvO3S1RJARq2zUgxtVyrLkvtBTgG3ewe9BxyYUqy9Q4DVilm48itDh7JAHX6cDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2a0de66cad9dd1a9ff6cb780eeb61d3053ab66ce03ff1ae7023505e3cc72bed5","last_reissued_at":"2026-05-18T00:24:46.537076Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:24:46.537076Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1801.09870","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":"2026-05-18T00:24:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1C710K1gAncv9v/Nc8vzmnCb6rFY8HpvOGlXASCdUD8hNnetMJ3GRGIVSAyaWFAlyhlaJCB4FQ8CKuxuGR28Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T06:08:54.802002Z"},"content_sha256":"82c3d101404fa792861b1b0f2ff12f1ce11b7b8b0079d09b3864466d2876cbef","schema_version":"1.0","event_id":"sha256:82c3d101404fa792861b1b0f2ff12f1ce11b7b8b0079d09b3864466d2876cbef"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:FIG6M3FNTXI2T73MW6AO5NQ5GB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fast Power system security analysis with Guided Dropout","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"2), (2) LRI), Antoine Marot, Benjamin Donnot (1, Isabelle Guyon (1), Marc Schoenauer (1), Patrick Panciatici ((1) TAU","submitted_at":"2018-01-30T07:10:36Z","abstract_excerpt":"We propose a new method to efficiently compute load-flows (the steady-state of the power-grid for given productions, consumptions and grid topology), substituting conventional simulators based on differential equation solvers. We use a deep feed-forward neural network trained with load-flows precomputed by simulation. Our architecture permits to train a network on so-called \"n-1\" problems, in which load flows are evaluated for every possible line disconnection, then generalize to \"n-2\" problems without retraining (a clear advantage because of the combinatorial nature of the problem). To that e"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.09870","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":""},"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":"2026-05-18T00:24:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5TRiOPwT3GmM0vTL4bOlG46trEg4MjGzRzn6RmyGQOvYgM+V00GCxanYiAPyOo8pdEgcTi828bCSEPI3+qdAAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T06:08:54.802370Z"},"content_sha256":"ec982e38cb983a913299c682bc32c0258baa8ed5711d1ed653ad5857b7f91431","schema_version":"1.0","event_id":"sha256:ec982e38cb983a913299c682bc32c0258baa8ed5711d1ed653ad5857b7f91431"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FIG6M3FNTXI2T73MW6AO5NQ5GB/bundle.json","state_url":"https://pith.science/pith/FIG6M3FNTXI2T73MW6AO5NQ5GB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FIG6M3FNTXI2T73MW6AO5NQ5GB/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":"2026-06-25T06:08:54Z","links":{"resolver":"https://pith.science/pith/FIG6M3FNTXI2T73MW6AO5NQ5GB","bundle":"https://pith.science/pith/FIG6M3FNTXI2T73MW6AO5NQ5GB/bundle.json","state":"https://pith.science/pith/FIG6M3FNTXI2T73MW6AO5NQ5GB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FIG6M3FNTXI2T73MW6AO5NQ5GB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:FIG6M3FNTXI2T73MW6AO5NQ5GB","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":"32e6c07f3c98ce4a1cfe6f3bb7e9f67ca91d7ca0cfdfd5722131934967c04906","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-01-30T07:10:36Z","title_canon_sha256":"03f400b07cd438c69b6ac4b48ee221ba796081d990c472cf495f2dd1e07a6dba"},"schema_version":"1.0","source":{"id":"1801.09870","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.09870","created_at":"2026-05-18T00:24:46Z"},{"alias_kind":"arxiv_version","alias_value":"1801.09870v1","created_at":"2026-05-18T00:24:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.09870","created_at":"2026-05-18T00:24:46Z"},{"alias_kind":"pith_short_12","alias_value":"FIG6M3FNTXI2","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"FIG6M3FNTXI2T73M","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"FIG6M3FN","created_at":"2026-05-18T12:32:22Z"}],"graph_snapshots":[{"event_id":"sha256:ec982e38cb983a913299c682bc32c0258baa8ed5711d1ed653ad5857b7f91431","target":"graph","created_at":"2026-05-18T00:24:46Z","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":"We propose a new method to efficiently compute load-flows (the steady-state of the power-grid for given productions, consumptions and grid topology), substituting conventional simulators based on differential equation solvers. We use a deep feed-forward neural network trained with load-flows precomputed by simulation. Our architecture permits to train a network on so-called \"n-1\" problems, in which load flows are evaluated for every possible line disconnection, then generalize to \"n-2\" problems without retraining (a clear advantage because of the combinatorial nature of the problem). To that e","authors_text":"2), (2) LRI), Antoine Marot, Benjamin Donnot (1, Isabelle Guyon (1), Marc Schoenauer (1), Patrick Panciatici ((1) TAU","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-01-30T07:10:36Z","title":"Fast Power system security analysis with Guided Dropout"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.09870","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":"sha256:82c3d101404fa792861b1b0f2ff12f1ce11b7b8b0079d09b3864466d2876cbef","target":"record","created_at":"2026-05-18T00:24:46Z","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":"32e6c07f3c98ce4a1cfe6f3bb7e9f67ca91d7ca0cfdfd5722131934967c04906","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-01-30T07:10:36Z","title_canon_sha256":"03f400b07cd438c69b6ac4b48ee221ba796081d990c472cf495f2dd1e07a6dba"},"schema_version":"1.0","source":{"id":"1801.09870","kind":"arxiv","version":1}},"canonical_sha256":"2a0de66cad9dd1a9ff6cb780eeb61d3053ab66ce03ff1ae7023505e3cc72bed5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2a0de66cad9dd1a9ff6cb780eeb61d3053ab66ce03ff1ae7023505e3cc72bed5","first_computed_at":"2026-05-18T00:24:46.537076Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:24:46.537076Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8eKnBDRN695oYBXHHtKIMiucvO3S1RJARq2zUgxtVyrLkvtBTgG3ewe9BxyYUqy9Q4DVilm48itDh7JAHX6cDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:24:46.537708Z","signed_message":"canonical_sha256_bytes"},"source_id":"1801.09870","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:82c3d101404fa792861b1b0f2ff12f1ce11b7b8b0079d09b3864466d2876cbef","sha256:ec982e38cb983a913299c682bc32c0258baa8ed5711d1ed653ad5857b7f91431"],"state_sha256":"197dc4c0398fa5451042c4852a7082b3a34bbc30d54d399314ecd1cbd3daa6cf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OXUkISA2BGd+4X1bzlRW8KrkJNd0ea3V3lc+WicffmKtUV5dj/IE6mtetlBCBTHy0zq8pgSwazYyQr9X70M+CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-25T06:08:54.804322Z","bundle_sha256":"341ea18b59a744a78898b061fe0f606fd70e72526807e1898eaef4a829fcb4df"}}