{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:MM5EE75Q5QUMGFMMU6MVL4SLDX","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":"d02a44b9a498c9b179811c10ef7ac21d4b6bf7432d626ce5ba3e6072606e81ea","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-05T09:30:56Z","title_canon_sha256":"4359f91d829235a17d4107908244cf48699ad94747c9bbd1328631d25dc6cfbc"},"schema_version":"1.0","source":{"id":"2110.01894","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.01894","created_at":"2026-07-05T05:51:55Z"},{"alias_kind":"arxiv_version","alias_value":"2110.01894v2","created_at":"2026-07-05T05:51:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.01894","created_at":"2026-07-05T05:51:55Z"},{"alias_kind":"pith_short_12","alias_value":"MM5EE75Q5QUM","created_at":"2026-07-05T05:51:55Z"},{"alias_kind":"pith_short_16","alias_value":"MM5EE75Q5QUMGFMM","created_at":"2026-07-05T05:51:55Z"},{"alias_kind":"pith_short_8","alias_value":"MM5EE75Q","created_at":"2026-07-05T05:51:55Z"}],"graph_snapshots":[{"event_id":"sha256:bbd67de364556db057fe6407350b2d615ae0b8f79a416a6d6badb988bb410e47","target":"graph","created_at":"2026-07-05T05:51:55Z","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/2110.01894/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning has been widely used within learning algorithms for robotics. One disadvantage of deep networks is that these networks are black-box representations. Therefore, the learned approximations ignore the existing knowledge of physics or robotics. Especially for learning dynamics models, these black-box models are not desirable as the underlying principles are well understood and the standard deep networks can learn dynamics that violate these principles. To learn dynamics models with deep networks that guarantee physically plausible dynamics, we introduce physics-inspired deep network","authors_text":"Jan Peters, Michael Lutter","cross_cats":["cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-05T09:30:56Z","title":"Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.01894","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:fea6cb7a98b9c0434b7ab65ae2dc77c7f94274b368946ac1b8f68ac9ce219b21","target":"record","created_at":"2026-07-05T05:51:55Z","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":"d02a44b9a498c9b179811c10ef7ac21d4b6bf7432d626ce5ba3e6072606e81ea","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-05T09:30:56Z","title_canon_sha256":"4359f91d829235a17d4107908244cf48699ad94747c9bbd1328631d25dc6cfbc"},"schema_version":"1.0","source":{"id":"2110.01894","kind":"arxiv","version":2}},"canonical_sha256":"633a427fb0ec28c3158ca79955f24b1de473266b90ceb1d99f30a16f1dc06608","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"633a427fb0ec28c3158ca79955f24b1de473266b90ceb1d99f30a16f1dc06608","first_computed_at":"2026-07-05T05:51:55.167557Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:51:55.167557Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WchpmMd5UyfFetm3oiEIxDXgtkVik8GGwNM1PftNGuQqPGM0Wt/b4JFCE9uUyWAdUQD6c1PHjKF+QYCXLSdBAg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:51:55.167949Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.01894","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fea6cb7a98b9c0434b7ab65ae2dc77c7f94274b368946ac1b8f68ac9ce219b21","sha256:bbd67de364556db057fe6407350b2d615ae0b8f79a416a6d6badb988bb410e47"],"state_sha256":"9fcef4cae996548283ea9ac70136ca21b08ed87482272cf69bc7d90caa1e6023"}