{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:4O2SKALL35NJCD4E6XKQ42F4PS","short_pith_number":"pith:4O2SKALL","canonical_record":{"source":{"id":"2412.17499","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-23T11:56:35Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"9d1ac3f0c0c633d92852b4cc3f2240bec95ea3f5025bcf2fbee88fcb6501afa9","abstract_canon_sha256":"531fd5001fee0d71efead0d0ff446f8df81a70d1eb11b13d66d2746566f2869c"},"schema_version":"1.0"},"canonical_sha256":"e3b525016bdf5a910f84f5d50e68bc7c8343a3ac031833518499905b6403703a","source":{"kind":"arxiv","id":"2412.17499","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.17499","created_at":"2026-07-05T11:19:02Z"},{"alias_kind":"arxiv_version","alias_value":"2412.17499v2","created_at":"2026-07-05T11:19:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.17499","created_at":"2026-07-05T11:19:02Z"},{"alias_kind":"pith_short_12","alias_value":"4O2SKALL35NJ","created_at":"2026-07-05T11:19:02Z"},{"alias_kind":"pith_short_16","alias_value":"4O2SKALL35NJCD4E","created_at":"2026-07-05T11:19:02Z"},{"alias_kind":"pith_short_8","alias_value":"4O2SKALL","created_at":"2026-07-05T11:19:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:4O2SKALL35NJCD4E6XKQ42F4PS","target":"record","payload":{"canonical_record":{"source":{"id":"2412.17499","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-23T11:56:35Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"9d1ac3f0c0c633d92852b4cc3f2240bec95ea3f5025bcf2fbee88fcb6501afa9","abstract_canon_sha256":"531fd5001fee0d71efead0d0ff446f8df81a70d1eb11b13d66d2746566f2869c"},"schema_version":"1.0"},"canonical_sha256":"e3b525016bdf5a910f84f5d50e68bc7c8343a3ac031833518499905b6403703a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:19:02.401053Z","signature_b64":"hZ/Tj/f2bRICrysEclaNz8eBZzAv8g8pSEW3uBIp4X8PP23ZQT6R+qScipPAAr+y8ike+vRu9N6RX4KgQdzWDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e3b525016bdf5a910f84f5d50e68bc7c8343a3ac031833518499905b6403703a","last_reissued_at":"2026-07-05T11:19:02.400538Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:19:02.400538Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.17499","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:19:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AvVtRAuUIeJhOTphbHG9PUQxNhe1WHQzInK1g1qKsXz7CTZgrbrLJycs5kxJPzQpJ8HeBz6p/IO1ZTcp082yCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T13:41:04.567026Z"},"content_sha256":"47514dd9cde5ec7d08f66fbc30239c7dfe232a26324d4c05757c0b67828f72f8","schema_version":"1.0","event_id":"sha256:47514dd9cde5ec7d08f66fbc30239c7dfe232a26324d4c05757c0b67828f72f8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:4O2SKALL35NJCD4E6XKQ42F4PS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving the Noise Estimation of Latent Neural Stochastic Differential Equations","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Linus Heck, Maximilian Gelbrecht, Michael T. Schaub, Niklas Boers","submitted_at":"2024-12-23T11:56:35Z","abstract_excerpt":"Latent neural stochastic differential equations (SDEs) have recently emerged as a promising approach for learning generative models from stochastic time series data. However, they systematically underestimate the noise level inherent in such data, limiting their ability to capture stochastic dynamics accurately. We investigate this underestimation in detail and propose a straightforward solution: by including an explicit additional noise regularization in the loss function, we are able to learn a model that accurately captures the diffusion component of the data. We demonstrate our results on "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.17499","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2412.17499/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:19:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dLNGGBZ+VA8cRAuL/VwFh1bHd3oLSEo2Ka+eQ8Yiv1qN+9UgDNQsnLGq1n4+iO8nq6d+h+T80IAQXSceprN7CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T13:41:04.567493Z"},"content_sha256":"6873ce7544a852c686b46577d6b972b02c31a32cfad6f71af9bf9644fc4b3609","schema_version":"1.0","event_id":"sha256:6873ce7544a852c686b46577d6b972b02c31a32cfad6f71af9bf9644fc4b3609"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4O2SKALL35NJCD4E6XKQ42F4PS/bundle.json","state_url":"https://pith.science/pith/4O2SKALL35NJCD4E6XKQ42F4PS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4O2SKALL35NJCD4E6XKQ42F4PS/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-13T13:41:04Z","links":{"resolver":"https://pith.science/pith/4O2SKALL35NJCD4E6XKQ42F4PS","bundle":"https://pith.science/pith/4O2SKALL35NJCD4E6XKQ42F4PS/bundle.json","state":"https://pith.science/pith/4O2SKALL35NJCD4E6XKQ42F4PS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4O2SKALL35NJCD4E6XKQ42F4PS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4O2SKALL35NJCD4E6XKQ42F4PS","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":"531fd5001fee0d71efead0d0ff446f8df81a70d1eb11b13d66d2746566f2869c","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-23T11:56:35Z","title_canon_sha256":"9d1ac3f0c0c633d92852b4cc3f2240bec95ea3f5025bcf2fbee88fcb6501afa9"},"schema_version":"1.0","source":{"id":"2412.17499","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.17499","created_at":"2026-07-05T11:19:02Z"},{"alias_kind":"arxiv_version","alias_value":"2412.17499v2","created_at":"2026-07-05T11:19:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.17499","created_at":"2026-07-05T11:19:02Z"},{"alias_kind":"pith_short_12","alias_value":"4O2SKALL35NJ","created_at":"2026-07-05T11:19:02Z"},{"alias_kind":"pith_short_16","alias_value":"4O2SKALL35NJCD4E","created_at":"2026-07-05T11:19:02Z"},{"alias_kind":"pith_short_8","alias_value":"4O2SKALL","created_at":"2026-07-05T11:19:02Z"}],"graph_snapshots":[{"event_id":"sha256:6873ce7544a852c686b46577d6b972b02c31a32cfad6f71af9bf9644fc4b3609","target":"graph","created_at":"2026-07-05T11:19:02Z","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/2412.17499/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Latent neural stochastic differential equations (SDEs) have recently emerged as a promising approach for learning generative models from stochastic time series data. However, they systematically underestimate the noise level inherent in such data, limiting their ability to capture stochastic dynamics accurately. We investigate this underestimation in detail and propose a straightforward solution: by including an explicit additional noise regularization in the loss function, we are able to learn a model that accurately captures the diffusion component of the data. We demonstrate our results on ","authors_text":"Linus Heck, Maximilian Gelbrecht, Michael T. Schaub, Niklas Boers","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-23T11:56:35Z","title":"Improving the Noise Estimation of Latent Neural Stochastic Differential Equations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.17499","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":"sha256:47514dd9cde5ec7d08f66fbc30239c7dfe232a26324d4c05757c0b67828f72f8","target":"record","created_at":"2026-07-05T11:19:02Z","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":"531fd5001fee0d71efead0d0ff446f8df81a70d1eb11b13d66d2746566f2869c","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-23T11:56:35Z","title_canon_sha256":"9d1ac3f0c0c633d92852b4cc3f2240bec95ea3f5025bcf2fbee88fcb6501afa9"},"schema_version":"1.0","source":{"id":"2412.17499","kind":"arxiv","version":2}},"canonical_sha256":"e3b525016bdf5a910f84f5d50e68bc7c8343a3ac031833518499905b6403703a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e3b525016bdf5a910f84f5d50e68bc7c8343a3ac031833518499905b6403703a","first_computed_at":"2026-07-05T11:19:02.400538Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:19:02.400538Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hZ/Tj/f2bRICrysEclaNz8eBZzAv8g8pSEW3uBIp4X8PP23ZQT6R+qScipPAAr+y8ike+vRu9N6RX4KgQdzWDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:19:02.401053Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.17499","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:47514dd9cde5ec7d08f66fbc30239c7dfe232a26324d4c05757c0b67828f72f8","sha256:6873ce7544a852c686b46577d6b972b02c31a32cfad6f71af9bf9644fc4b3609"],"state_sha256":"9818d3ff04d298f6d7027a5f1af0bd10b672f59283712342a05689fb5bc9b56d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BPH7qSKAkG9+YtogKZQR/kXeNAvukM9fYvRRmSolicmUw9qHAMvVWt339V/AQCQkUhKRnKxElsw54scQ9RGZBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T13:41:04.570534Z","bundle_sha256":"17222b29405be25f64dd9a299d9d809544adc9a4ecb55b55f4f2dd008c91e934"}}