{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:U3RKLUWUDR7B7KYVEYVOSXCYNL","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":"153908d095861b6ae33b936bad357590dd9877c4148c0637a940976e50110e50","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-02-22T22:12:56Z","title_canon_sha256":"2f92c8207a80e491503f9e2b35711f86c1b311e17af6e097283d6c98165682b3"},"schema_version":"1.0","source":{"id":"2002.09779","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.09779","created_at":"2026-07-05T01:13:43Z"},{"alias_kind":"arxiv_version","alias_value":"2002.09779v2","created_at":"2026-07-05T01:13:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.09779","created_at":"2026-07-05T01:13:43Z"},{"alias_kind":"pith_short_12","alias_value":"U3RKLUWUDR7B","created_at":"2026-07-05T01:13:43Z"},{"alias_kind":"pith_short_16","alias_value":"U3RKLUWUDR7B7KYV","created_at":"2026-07-05T01:13:43Z"},{"alias_kind":"pith_short_8","alias_value":"U3RKLUWU","created_at":"2026-07-05T01:13:43Z"}],"graph_snapshots":[{"event_id":"sha256:7886ef18a69e96a812b5caff9733bbcaef52bc6a17f27ebb0545ed26953b26e5","target":"graph","created_at":"2026-07-05T01:13:43Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2002.09779/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Stochastic regularization of neural networks (e.g. dropout) is a wide-spread technique in deep learning that allows for better generalization. Despite its success, continuous-time models, such as neural ordinary differential equation (ODE), usually rely on a completely deterministic feed-forward operation. This work provides an empirical study of stochastically regularized neural ODE on several image-classification tasks (CIFAR-10, CIFAR-100, TinyImageNet). Building upon the formalism of stochastic differential equations (SDEs), we demonstrate that neural SDE is able to outperform its determin","authors_text":"Alexandra Volokhova, Dmitry Vetrov, Viktor Oganesyan","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-02-22T22:12:56Z","title":"Stochasticity in Neural ODEs: An Empirical Study"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.09779","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:e3e584776f2fc9147afb979e20bcd429729b48f56174fee9617cb3cc53fc836e","target":"record","created_at":"2026-07-05T01:13:43Z","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":"153908d095861b6ae33b936bad357590dd9877c4148c0637a940976e50110e50","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-02-22T22:12:56Z","title_canon_sha256":"2f92c8207a80e491503f9e2b35711f86c1b311e17af6e097283d6c98165682b3"},"schema_version":"1.0","source":{"id":"2002.09779","kind":"arxiv","version":2}},"canonical_sha256":"a6e2a5d2d41c7e1fab15262ae95c586ae34ebf502846f2362df7015faef1154d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a6e2a5d2d41c7e1fab15262ae95c586ae34ebf502846f2362df7015faef1154d","first_computed_at":"2026-07-05T01:13:43.545824Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:13:43.545824Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MQNkKuuGcAuUfFuzgF6PQXzWTCi00Z2HDwiFQBRVznRGl0DU6ITEtxZOdW+JNguMYBQbCLTfKpQKU53yk2nfBA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:13:43.546290Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.09779","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e3e584776f2fc9147afb979e20bcd429729b48f56174fee9617cb3cc53fc836e","sha256:7886ef18a69e96a812b5caff9733bbcaef52bc6a17f27ebb0545ed26953b26e5"],"state_sha256":"d482296261fbaab2a6699e960dfa34f2c036bb5bfce8952a51ec98ccd6b70843"}