{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:ZNTHKIIIIUBERM6M4C3WJDYT2X","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":"6b0f5e6bb82155db3e8a382770b621f043c90cea35030b87c602c6867f582a02","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-01-25T07:14:40Z","title_canon_sha256":"e461bca02f2e595d068f6c4d1f3a93d0145271ffe1f78495d8df0cfd69fcaf5c"},"schema_version":"1.0","source":{"id":"1902.02627","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.02627","created_at":"2026-05-17T23:54:31Z"},{"alias_kind":"arxiv_version","alias_value":"1902.02627v2","created_at":"2026-05-17T23:54:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.02627","created_at":"2026-05-17T23:54:31Z"},{"alias_kind":"pith_short_12","alias_value":"ZNTHKIIIIUBE","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"ZNTHKIIIIUBERM6M","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"ZNTHKIII","created_at":"2026-05-18T12:33:33Z"}],"graph_snapshots":[{"event_id":"sha256:50638c4088936a014503ca347ace1ad4434dc18e06e17a480194d05bdd257bbf","target":"graph","created_at":"2026-05-17T23:54:31Z","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":"Generating eye diagrams by using a circuit simulator can be very computationally intensive, especially in the presence of nonlinearities. It often involves multiple Newton-like iterations at every time step when a SPICE-like circuit simulator handles a nonlinear system in the transient regime. In this paper, we leverage machine learning methods, to be specific, the recurrent neural network (RNN), to generate black-box macromodels and achieve significant reduction of computation time. Through the proposed approach, an RNN model is first trained and then validated on a relatively short sequence ","authors_text":"Jose Schutt-Aine, Ken Wu, Thong Nguyen, Tianjian Lu","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-01-25T07:14:40Z","title":"Fast Transient Simulation of High-Speed Channels Using Recurrent Neural Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.02627","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":"sha256:29e206b76437f60a6623e423f11cf061a813fd57de77a507b034bc72ff7ced7d","target":"record","created_at":"2026-05-17T23:54:31Z","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":"6b0f5e6bb82155db3e8a382770b621f043c90cea35030b87c602c6867f582a02","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-01-25T07:14:40Z","title_canon_sha256":"e461bca02f2e595d068f6c4d1f3a93d0145271ffe1f78495d8df0cfd69fcaf5c"},"schema_version":"1.0","source":{"id":"1902.02627","kind":"arxiv","version":2}},"canonical_sha256":"cb66752108450248b3cce0b7648f13d5d3a2275faa5e879c03f1067bf5f83834","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cb66752108450248b3cce0b7648f13d5d3a2275faa5e879c03f1067bf5f83834","first_computed_at":"2026-05-17T23:54:31.281678Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:54:31.281678Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"l+Lt3g6ZNpaZFGFdIKjZrpKttaMp95p/cGu2dO9csdfvkmpk6rcQiEylZ+f7nh1M+cQ/FxD/1ICb5nw2YujxBw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:54:31.282222Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.02627","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:29e206b76437f60a6623e423f11cf061a813fd57de77a507b034bc72ff7ced7d","sha256:50638c4088936a014503ca347ace1ad4434dc18e06e17a480194d05bdd257bbf"],"state_sha256":"711f9ef53c07482e7333ae3f639b83dca20c1827d636e8b1196c69e2d43cad5f"}