{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:Q5OYUMUF3D7RFNKY4YQYZSOBH4","short_pith_number":"pith:Q5OYUMUF","canonical_record":{"source":{"id":"2011.04583","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-11-09T17:28:23Z","cross_cats_sorted":[],"title_canon_sha256":"cb363d4a5c7f3124e12fbaa294845a4366548221b7a09ba6f807a4769ff87b6c","abstract_canon_sha256":"1ca2cbaddca6b1a34efbdaccdcfd92f472143a3cc0fa63afa895fd19043e52ef"},"schema_version":"1.0"},"canonical_sha256":"875d8a3285d8ff12b558e6218cc9c13f3693f408b027f6c9d44a744a6397e7df","source":{"kind":"arxiv","id":"2011.04583","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.04583","created_at":"2026-07-05T02:24:11Z"},{"alias_kind":"arxiv_version","alias_value":"2011.04583v3","created_at":"2026-07-05T02:24:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.04583","created_at":"2026-07-05T02:24:11Z"},{"alias_kind":"pith_short_12","alias_value":"Q5OYUMUF3D7R","created_at":"2026-07-05T02:24:11Z"},{"alias_kind":"pith_short_16","alias_value":"Q5OYUMUF3D7RFNKY","created_at":"2026-07-05T02:24:11Z"},{"alias_kind":"pith_short_8","alias_value":"Q5OYUMUF","created_at":"2026-07-05T02:24:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:Q5OYUMUF3D7RFNKY4YQYZSOBH4","target":"record","payload":{"canonical_record":{"source":{"id":"2011.04583","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-11-09T17:28:23Z","cross_cats_sorted":[],"title_canon_sha256":"cb363d4a5c7f3124e12fbaa294845a4366548221b7a09ba6f807a4769ff87b6c","abstract_canon_sha256":"1ca2cbaddca6b1a34efbdaccdcfd92f472143a3cc0fa63afa895fd19043e52ef"},"schema_version":"1.0"},"canonical_sha256":"875d8a3285d8ff12b558e6218cc9c13f3693f408b027f6c9d44a744a6397e7df","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:24:11.938206Z","signature_b64":"otuExQP5SEJPDDTuFuMOQR94G7+gfpPIeasNZ8PBsLxE6owkPn972eMPRcZTrLVzaHEgfyJCVTGAsfGCahnRCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"875d8a3285d8ff12b558e6218cc9c13f3693f408b027f6c9d44a744a6397e7df","last_reissued_at":"2026-07-05T02:24:11.937657Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:24:11.937657Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2011.04583","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:24:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vHeczBu78rCjmUvg5Ic75OvUg7Lp5NHZuQzkDt0AF0FyZ8xFfkPpTPvjxBUvP5jw8M5rO+H6b4QHbqqDp5mGBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T21:24:55.203149Z"},"content_sha256":"da3854fdf8cb0ae2e56718bb82a97b2a163e53fc998346ea87708123f8ec60d5","schema_version":"1.0","event_id":"sha256:da3854fdf8cb0ae2e56718bb82a97b2a163e53fc998346ea87708123f8ec60d5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:Q5OYUMUF3D7RFNKY4YQYZSOBH4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural Spatio-Temporal Point Processes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Brandon Amos, Maximilian Nickel, Ricky T. Q. Chen","submitted_at":"2020-11-09T17:28:23Z","abstract_excerpt":"We propose a new class of parameterizations for spatio-temporal point processes which leverage Neural ODEs as a computational method and enable flexible, high-fidelity models of discrete events that are localized in continuous time and space. Central to our approach is a combination of continuous-time neural networks with two novel neural architectures, i.e., Jump and Attentive Continuous-time Normalizing Flows. This approach allows us to learn complex distributions for both the spatial and temporal domain and to condition non-trivially on the observed event history. We validate our models on "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.04583","kind":"arxiv","version":3},"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/2011.04583/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":"2026-07-05T02:24:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ta5Tfa3NLk+RuLdzACUo6emUdWqiehdbPsuLJbVb9atgOs7y/rz04YfcMPuPZ9P+LLy5hG/JvESoMksuoUiQCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T21:24:55.203655Z"},"content_sha256":"71d4ba506a8482ebf03e72e8379b94c8109525b6d93dd5fb9b52caeaa0eb1962","schema_version":"1.0","event_id":"sha256:71d4ba506a8482ebf03e72e8379b94c8109525b6d93dd5fb9b52caeaa0eb1962"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q5OYUMUF3D7RFNKY4YQYZSOBH4/bundle.json","state_url":"https://pith.science/pith/Q5OYUMUF3D7RFNKY4YQYZSOBH4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q5OYUMUF3D7RFNKY4YQYZSOBH4/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":"2026-08-23T21:24:55Z","links":{"resolver":"https://pith.science/pith/Q5OYUMUF3D7RFNKY4YQYZSOBH4","bundle":"https://pith.science/pith/Q5OYUMUF3D7RFNKY4YQYZSOBH4/bundle.json","state":"https://pith.science/pith/Q5OYUMUF3D7RFNKY4YQYZSOBH4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q5OYUMUF3D7RFNKY4YQYZSOBH4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:Q5OYUMUF3D7RFNKY4YQYZSOBH4","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":"1ca2cbaddca6b1a34efbdaccdcfd92f472143a3cc0fa63afa895fd19043e52ef","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-11-09T17:28:23Z","title_canon_sha256":"cb363d4a5c7f3124e12fbaa294845a4366548221b7a09ba6f807a4769ff87b6c"},"schema_version":"1.0","source":{"id":"2011.04583","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.04583","created_at":"2026-07-05T02:24:11Z"},{"alias_kind":"arxiv_version","alias_value":"2011.04583v3","created_at":"2026-07-05T02:24:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.04583","created_at":"2026-07-05T02:24:11Z"},{"alias_kind":"pith_short_12","alias_value":"Q5OYUMUF3D7R","created_at":"2026-07-05T02:24:11Z"},{"alias_kind":"pith_short_16","alias_value":"Q5OYUMUF3D7RFNKY","created_at":"2026-07-05T02:24:11Z"},{"alias_kind":"pith_short_8","alias_value":"Q5OYUMUF","created_at":"2026-07-05T02:24:11Z"}],"graph_snapshots":[{"event_id":"sha256:71d4ba506a8482ebf03e72e8379b94c8109525b6d93dd5fb9b52caeaa0eb1962","target":"graph","created_at":"2026-07-05T02:24:11Z","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/2011.04583/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose a new class of parameterizations for spatio-temporal point processes which leverage Neural ODEs as a computational method and enable flexible, high-fidelity models of discrete events that are localized in continuous time and space. Central to our approach is a combination of continuous-time neural networks with two novel neural architectures, i.e., Jump and Attentive Continuous-time Normalizing Flows. This approach allows us to learn complex distributions for both the spatial and temporal domain and to condition non-trivially on the observed event history. We validate our models on ","authors_text":"Brandon Amos, Maximilian Nickel, Ricky T. Q. Chen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-11-09T17:28:23Z","title":"Neural Spatio-Temporal Point Processes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.04583","kind":"arxiv","version":3},"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:da3854fdf8cb0ae2e56718bb82a97b2a163e53fc998346ea87708123f8ec60d5","target":"record","created_at":"2026-07-05T02:24:11Z","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":"1ca2cbaddca6b1a34efbdaccdcfd92f472143a3cc0fa63afa895fd19043e52ef","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-11-09T17:28:23Z","title_canon_sha256":"cb363d4a5c7f3124e12fbaa294845a4366548221b7a09ba6f807a4769ff87b6c"},"schema_version":"1.0","source":{"id":"2011.04583","kind":"arxiv","version":3}},"canonical_sha256":"875d8a3285d8ff12b558e6218cc9c13f3693f408b027f6c9d44a744a6397e7df","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"875d8a3285d8ff12b558e6218cc9c13f3693f408b027f6c9d44a744a6397e7df","first_computed_at":"2026-07-05T02:24:11.937657Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:24:11.937657Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"otuExQP5SEJPDDTuFuMOQR94G7+gfpPIeasNZ8PBsLxE6owkPn972eMPRcZTrLVzaHEgfyJCVTGAsfGCahnRCA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:24:11.938206Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.04583","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:da3854fdf8cb0ae2e56718bb82a97b2a163e53fc998346ea87708123f8ec60d5","sha256:71d4ba506a8482ebf03e72e8379b94c8109525b6d93dd5fb9b52caeaa0eb1962"],"state_sha256":"e0bf7dc8f29af62ab9b51372d34d4d878a798b600428a746d4a330fa5ea9004a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ULBM5yVPKHe+K3rrffj0lfQTmsDp39msxO2tbEGffluCOHVVbV5ZTLZCYGdjOG0j2nCiAkyvViB/URkYAzqcAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T21:24:55.207872Z","bundle_sha256":"56ea4842100dcdf2fb83d5b83793a6b6c71945869387cdf64c71fc0f915d3169"}}