{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:MS6NNGGVWAYWTCNAHSPUHGM2G4","short_pith_number":"pith:MS6NNGGV","canonical_record":{"source":{"id":"2309.07200","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-13T15:59:14Z","cross_cats_sorted":["cs.AI","cs.IT","math.IT"],"title_canon_sha256":"410aedd86d9b8369b2bb9420734d4ba0b24a198dbb9f21d357b594df85e2d394","abstract_canon_sha256":"47f6781e98eda5c57e4dcc71639b86181c51203656f6fd9a2e3eed18507a4d53"},"schema_version":"1.0"},"canonical_sha256":"64bcd698d5b0316989a03c9f43999a373358a6078bf0c6007c3ed8ee60dbee77","source":{"kind":"arxiv","id":"2309.07200","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.07200","created_at":"2026-07-05T07:37:51Z"},{"alias_kind":"arxiv_version","alias_value":"2309.07200v2","created_at":"2026-07-05T07:37:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.07200","created_at":"2026-07-05T07:37:51Z"},{"alias_kind":"pith_short_12","alias_value":"MS6NNGGVWAYW","created_at":"2026-07-05T07:37:51Z"},{"alias_kind":"pith_short_16","alias_value":"MS6NNGGVWAYWTCNA","created_at":"2026-07-05T07:37:51Z"},{"alias_kind":"pith_short_8","alias_value":"MS6NNGGV","created_at":"2026-07-05T07:37:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:MS6NNGGVWAYWTCNAHSPUHGM2G4","target":"record","payload":{"canonical_record":{"source":{"id":"2309.07200","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-13T15:59:14Z","cross_cats_sorted":["cs.AI","cs.IT","math.IT"],"title_canon_sha256":"410aedd86d9b8369b2bb9420734d4ba0b24a198dbb9f21d357b594df85e2d394","abstract_canon_sha256":"47f6781e98eda5c57e4dcc71639b86181c51203656f6fd9a2e3eed18507a4d53"},"schema_version":"1.0"},"canonical_sha256":"64bcd698d5b0316989a03c9f43999a373358a6078bf0c6007c3ed8ee60dbee77","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:37:51.702692Z","signature_b64":"Ce3MCQlGd1l7jWEjiNUUXXT/l1lBfQGIXPzy4XsAKX6nX8JRlz7G+DZFphlyjtK/0PbOdRMBtL/hsaWnyKNvBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"64bcd698d5b0316989a03c9f43999a373358a6078bf0c6007c3ed8ee60dbee77","last_reissued_at":"2026-07-05T07:37:51.702177Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:37:51.702177Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2309.07200","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":"2026-07-05T07:37:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3sbxOsA4nSOfZ2I+XAID+hEisp3vnW7LrX9t4kf+7xEK6g5sVoY7csTviOwpaRlTNhdmBfWIf2G3L/4b8eXWAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:54:29.604229Z"},"content_sha256":"c13543c17c462c6bcb9ba5c75be6439b6ace9bf663a66af6d3c91e4a03d258a2","schema_version":"1.0","event_id":"sha256:c13543c17c462c6bcb9ba5c75be6439b6ace9bf663a66af6d3c91e4a03d258a2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:MS6NNGGVWAYWTCNAHSPUHGM2G4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.IT","math.IT"],"primary_cat":"cs.LG","authors_text":"Bastiaan S. Veeling, Marco Federici, Patrick Forr\\'e, Ryota Tomioka","submitted_at":"2023-09-13T15:59:14Z","abstract_excerpt":"Markov processes are widely used mathematical models for describing dynamic systems in various fields. However, accurately simulating large-scale systems at long time scales is computationally expensive due to the short time steps required for accurate integration. In this paper, we introduce an inference process that maps complex systems into a simplified representational space and models large jumps in time. To achieve this, we propose Time-lagged Information Bottleneck (T-IB), a principled objective rooted in information theory, which aims to capture relevant temporal features while discard"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.07200","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/2309.07200/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":"2026-07-05T07:37:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c0fxTDYI3kNy42Qn8MyIjASwSYPla51FjzD9F1P/hHR6VZz/DCfTaupvXiIn1pFI3sL3c+RFAA82WpFTOteDDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:54:29.605260Z"},"content_sha256":"d53ea7557fb29f5d320c8795f4dec4509921288fb54788db8f17d38c0b1419f9","schema_version":"1.0","event_id":"sha256:d53ea7557fb29f5d320c8795f4dec4509921288fb54788db8f17d38c0b1419f9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MS6NNGGVWAYWTCNAHSPUHGM2G4/bundle.json","state_url":"https://pith.science/pith/MS6NNGGVWAYWTCNAHSPUHGM2G4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MS6NNGGVWAYWTCNAHSPUHGM2G4/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":"2026-08-08T04:54:29Z","links":{"resolver":"https://pith.science/pith/MS6NNGGVWAYWTCNAHSPUHGM2G4","bundle":"https://pith.science/pith/MS6NNGGVWAYWTCNAHSPUHGM2G4/bundle.json","state":"https://pith.science/pith/MS6NNGGVWAYWTCNAHSPUHGM2G4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MS6NNGGVWAYWTCNAHSPUHGM2G4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:MS6NNGGVWAYWTCNAHSPUHGM2G4","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":"47f6781e98eda5c57e4dcc71639b86181c51203656f6fd9a2e3eed18507a4d53","cross_cats_sorted":["cs.AI","cs.IT","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-13T15:59:14Z","title_canon_sha256":"410aedd86d9b8369b2bb9420734d4ba0b24a198dbb9f21d357b594df85e2d394"},"schema_version":"1.0","source":{"id":"2309.07200","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.07200","created_at":"2026-07-05T07:37:51Z"},{"alias_kind":"arxiv_version","alias_value":"2309.07200v2","created_at":"2026-07-05T07:37:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.07200","created_at":"2026-07-05T07:37:51Z"},{"alias_kind":"pith_short_12","alias_value":"MS6NNGGVWAYW","created_at":"2026-07-05T07:37:51Z"},{"alias_kind":"pith_short_16","alias_value":"MS6NNGGVWAYWTCNA","created_at":"2026-07-05T07:37:51Z"},{"alias_kind":"pith_short_8","alias_value":"MS6NNGGV","created_at":"2026-07-05T07:37:51Z"}],"graph_snapshots":[{"event_id":"sha256:d53ea7557fb29f5d320c8795f4dec4509921288fb54788db8f17d38c0b1419f9","target":"graph","created_at":"2026-07-05T07:37:51Z","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/2309.07200/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Markov processes are widely used mathematical models for describing dynamic systems in various fields. However, accurately simulating large-scale systems at long time scales is computationally expensive due to the short time steps required for accurate integration. In this paper, we introduce an inference process that maps complex systems into a simplified representational space and models large jumps in time. To achieve this, we propose Time-lagged Information Bottleneck (T-IB), a principled objective rooted in information theory, which aims to capture relevant temporal features while discard","authors_text":"Bastiaan S. Veeling, Marco Federici, Patrick Forr\\'e, Ryota Tomioka","cross_cats":["cs.AI","cs.IT","math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-13T15:59:14Z","title":"Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.07200","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:c13543c17c462c6bcb9ba5c75be6439b6ace9bf663a66af6d3c91e4a03d258a2","target":"record","created_at":"2026-07-05T07:37:51Z","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":"47f6781e98eda5c57e4dcc71639b86181c51203656f6fd9a2e3eed18507a4d53","cross_cats_sorted":["cs.AI","cs.IT","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-13T15:59:14Z","title_canon_sha256":"410aedd86d9b8369b2bb9420734d4ba0b24a198dbb9f21d357b594df85e2d394"},"schema_version":"1.0","source":{"id":"2309.07200","kind":"arxiv","version":2}},"canonical_sha256":"64bcd698d5b0316989a03c9f43999a373358a6078bf0c6007c3ed8ee60dbee77","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"64bcd698d5b0316989a03c9f43999a373358a6078bf0c6007c3ed8ee60dbee77","first_computed_at":"2026-07-05T07:37:51.702177Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:37:51.702177Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ce3MCQlGd1l7jWEjiNUUXXT/l1lBfQGIXPzy4XsAKX6nX8JRlz7G+DZFphlyjtK/0PbOdRMBtL/hsaWnyKNvBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:37:51.702692Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.07200","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c13543c17c462c6bcb9ba5c75be6439b6ace9bf663a66af6d3c91e4a03d258a2","sha256:d53ea7557fb29f5d320c8795f4dec4509921288fb54788db8f17d38c0b1419f9"],"state_sha256":"89c0a125fd596c7a829c6986fe6936217110c21d3c8e2cf702039bd6dbf54173"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DIIZbNqmg4G8yOWSrLkja/Ou9kikJrtYzOXYOFIVnjV9pW0P/dzH2IHzsQcRWDhMY9MayZFRj9fciI9eoMtoDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T04:54:29.610905Z","bundle_sha256":"0a236117eb53168494f860aa4008b6e2806f2e71e9dad5f6bb1e9374cd3de00b"}}