{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:TBUTMW6JEF6Z2GG5JFIJUGFTFG","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":"cba52ec6a3fd66e532fab34fed2302cf15e1e6f37253015917d09375e028f927","cross_cats_sorted":["cs.LG","cs.RO","cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-07-29T21:14:34Z","title_canon_sha256":"38de70c70c32bb45cb13acea196ef97f99707abeb695cb30fba23c0677fa8fbc"},"schema_version":"1.0","source":{"id":"1907.13122","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.13122","created_at":"2026-07-04T23:50:46Z"},{"alias_kind":"arxiv_version","alias_value":"1907.13122v1","created_at":"2026-07-04T23:50:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.13122","created_at":"2026-07-04T23:50:46Z"},{"alias_kind":"pith_short_12","alias_value":"TBUTMW6JEF6Z","created_at":"2026-07-04T23:50:46Z"},{"alias_kind":"pith_short_16","alias_value":"TBUTMW6JEF6Z2GG5","created_at":"2026-07-04T23:50:46Z"},{"alias_kind":"pith_short_8","alias_value":"TBUTMW6J","created_at":"2026-07-04T23:50:46Z"}],"graph_snapshots":[{"event_id":"sha256:25b0a87e0926de3bc274ca488d580da46c4495676067254c6bbf53c321435fc1","target":"graph","created_at":"2026-07-04T23:50:46Z","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/1907.13122/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose a novel framework for learning stabilizable nonlinear dynamical systems for continuous control tasks in robotics. The key contribution is a control-theoretic regularizer for dynamics fitting rooted in the notion of stabilizability, a constraint which guarantees the existence of robust tracking controllers for arbitrary open-loop trajectories generated with the learned system. Leveraging tools from contraction theory and statistical learning in Reproducing Kernel Hilbert Spaces, we formulate stabilizable dynamics learning as a functional optimization with convex objective and bi-conv","authors_text":"Jean-Jacques E. Slotine, Marco Pavone, Spencer M. Richards, Sumeet Singh, Vikas Sindhwani","cross_cats":["cs.LG","cs.RO","cs.SY","eess.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-07-29T21:14:34Z","title":"Learning Stabilizable Nonlinear Dynamics with Contraction-Based Regularization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.13122","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:b122ae69a020f2fde2267735cd1f62270ba4de7c26dcea49d2c506571a4d6974","target":"record","created_at":"2026-07-04T23:50:46Z","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":"cba52ec6a3fd66e532fab34fed2302cf15e1e6f37253015917d09375e028f927","cross_cats_sorted":["cs.LG","cs.RO","cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-07-29T21:14:34Z","title_canon_sha256":"38de70c70c32bb45cb13acea196ef97f99707abeb695cb30fba23c0677fa8fbc"},"schema_version":"1.0","source":{"id":"1907.13122","kind":"arxiv","version":1}},"canonical_sha256":"9869365bc9217d9d18dd49509a18b329b069ba6c31d6cd8aecc76c980bd2726d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9869365bc9217d9d18dd49509a18b329b069ba6c31d6cd8aecc76c980bd2726d","first_computed_at":"2026-07-04T23:50:46.656971Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:50:46.656971Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Mzz4ckXqCSuT6bIn3q+4kg/V31vjan+tJwkUIZLWgrfX+23jVYlP1mHYWiyjGAzO6kVghiIWYGn0NwPktLFNCA==","signature_status":"signed_v1","signed_at":"2026-07-04T23:50:46.657432Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.13122","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b122ae69a020f2fde2267735cd1f62270ba4de7c26dcea49d2c506571a4d6974","sha256:25b0a87e0926de3bc274ca488d580da46c4495676067254c6bbf53c321435fc1"],"state_sha256":"01ca93851738ddfb4dbdf2cde18d41d32ce40ab71b1a2b5417ad54a8e6c3af0b"}