{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:ADRENMFBYV5BPX65BPJ5IQ3AGR","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":"400245a59e6acf0379b3cb6be6216bcfdc601ec486d16550f23da0e6c469cc0a","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-09-13T18:22:04Z","title_canon_sha256":"c81504d9868a8b9fdd3b41d55969042b0dbfca941bd42983634e5b3bd16bd306"},"schema_version":"1.0","source":{"id":"1809.05127","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.05127","created_at":"2026-05-18T00:05:44Z"},{"alias_kind":"arxiv_version","alias_value":"1809.05127v1","created_at":"2026-05-18T00:05:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.05127","created_at":"2026-05-18T00:05:44Z"},{"alias_kind":"pith_short_12","alias_value":"ADRENMFBYV5B","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"ADRENMFBYV5BPX65","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"ADRENMFB","created_at":"2026-05-18T12:32:13Z"}],"graph_snapshots":[{"event_id":"sha256:6b80e608b04440e509d336ba933aebdea12319e92bde17cda909ae220a7ffe47","target":"graph","created_at":"2026-05-18T00:05:44Z","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"},"paper":{"abstract_excerpt":"Deep neural networks (DNN) excel at extracting patterns. Through representation learning and automated feature engineering on large datasets, such models have been highly successful in computer vision and natural language applications. Designing optimal network architectures from a principled or rational approach however has been less than successful, with the best successful approaches utilizing an additional machine learning algorithm to tune the network hyperparameters. However, in many technical fields, there exist established domain knowledge and understanding about the subject matter. In","authors_text":"Garrett B. Goh, Jim Pfaendtner, Khushmeen Sakloth, Wesley Beckner","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-09-13T18:22:04Z","title":"IL-Net: Using Expert Knowledge to Guide the Design of Furcated Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.05127","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:ccbdd8c32a0f13c82aaf21a9742ee13a71c6b840793f0a781fdb369798ae7989","target":"record","created_at":"2026-05-18T00:05:44Z","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":"400245a59e6acf0379b3cb6be6216bcfdc601ec486d16550f23da0e6c469cc0a","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-09-13T18:22:04Z","title_canon_sha256":"c81504d9868a8b9fdd3b41d55969042b0dbfca941bd42983634e5b3bd16bd306"},"schema_version":"1.0","source":{"id":"1809.05127","kind":"arxiv","version":1}},"canonical_sha256":"00e246b0a1c57a17dfdd0bd3d4436034536970129b6a2ac5c792d32d0d7e2fd2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"00e246b0a1c57a17dfdd0bd3d4436034536970129b6a2ac5c792d32d0d7e2fd2","first_computed_at":"2026-05-18T00:05:44.688477Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:05:44.688477Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"V6USpi3mkchxPwLPChYKMcab0A+BpBBr80vsXgXwzy4xo0vOOmiCgCV8e7ImXF6EszbiJgeeC7HLRPwj8vyiDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:05:44.689225Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.05127","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ccbdd8c32a0f13c82aaf21a9742ee13a71c6b840793f0a781fdb369798ae7989","sha256:6b80e608b04440e509d336ba933aebdea12319e92bde17cda909ae220a7ffe47"],"state_sha256":"e8f628da35354d9e8f9dcd223f5c10ad2932cfaeb0e7b505483e5ef5f45db78c"}