{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:VSQJG3AN3BEQ67HVNC3KVCH2ZV","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":"db2c207847557601088fc1f05fd5407fd8f946f1ce64e7e26c049ec4cc5f08a4","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2017-10-16T13:58:08Z","title_canon_sha256":"224f0b47689d65fbb408ed128e71380f8034d9ba8abb831babb1162c59753bd7"},"schema_version":"1.0","source":{"id":"1710.05918","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.05918","created_at":"2026-05-18T00:32:38Z"},{"alias_kind":"arxiv_version","alias_value":"1710.05918v1","created_at":"2026-05-18T00:32:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.05918","created_at":"2026-05-18T00:32:38Z"},{"alias_kind":"pith_short_12","alias_value":"VSQJG3AN3BEQ","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_16","alias_value":"VSQJG3AN3BEQ67HV","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_8","alias_value":"VSQJG3AN","created_at":"2026-05-18T12:31:49Z"}],"graph_snapshots":[{"event_id":"sha256:6e996c0cf080ae49ba91a9047bfbf69089703bf37cf51a5849a6babe943a72da","target":"graph","created_at":"2026-05-18T00:32:38Z","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":"Convolutional Neural Networks (CNNs) are a popular deep learning architecture widely applied in different domains, in particular in classifying over images, for which the concept of convolution with a filter comes naturally. Unfortunately, the requirement of a distance (or, at least, of a neighbourhood function) in the input feature space has so far prevented its direct use on data types such as omics data. However, a number of omics data are metrizable, i.e., they can be endowed with a metric structure, enabling to adopt a convolutional based deep learning framework, e.g., for prediction. We ","authors_text":"Cesare Furlanello, Claudio Agostinelli, Diego Fioravanti, Giuseppe Jurman, Isotta Landi, Manlio De Domenico, Marco Chierici, Margherita Francescatto, Valerio Maggio, Ylenia Giarratano","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2017-10-16T13:58:08Z","title":"Convolutional neural networks for structured omics: OmicsCNN and the OmicsConv layer"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.05918","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":"sha256:14a28155c6d14062b8325f594ffee1db35e188257fdf0995ec98187784b5bf8b","target":"record","created_at":"2026-05-18T00:32:38Z","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":"db2c207847557601088fc1f05fd5407fd8f946f1ce64e7e26c049ec4cc5f08a4","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2017-10-16T13:58:08Z","title_canon_sha256":"224f0b47689d65fbb408ed128e71380f8034d9ba8abb831babb1162c59753bd7"},"schema_version":"1.0","source":{"id":"1710.05918","kind":"arxiv","version":1}},"canonical_sha256":"aca0936c0dd8490f7cf568b6aa88facd4982fef59c79207132f9e76cb5651cf5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aca0936c0dd8490f7cf568b6aa88facd4982fef59c79207132f9e76cb5651cf5","first_computed_at":"2026-05-18T00:32:38.321579Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:32:38.321579Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fwBvs1pkbXOXw4fsa4UFKLgketyLwQAFUPbuFFsWiYL+63UuGr6WOo0qSC62Evw45MOJqPWbHN4DO5m8lEI5Dg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:32:38.322274Z","signed_message":"canonical_sha256_bytes"},"source_id":"1710.05918","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:14a28155c6d14062b8325f594ffee1db35e188257fdf0995ec98187784b5bf8b","sha256:6e996c0cf080ae49ba91a9047bfbf69089703bf37cf51a5849a6babe943a72da"],"state_sha256":"cf75b1601cdcb5646decfa3408fc35277e9f47f3f60e019446778deb44beaebc"}