{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:2CRXAWPCWRVIFDNSWOIQMNBBBS","short_pith_number":"pith:2CRXAWPC","canonical_record":{"source":{"id":"2412.19517","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-27T08:19:23Z","cross_cats_sorted":["cs.AI","cs.NA","math.NA","q-bio.PE","stat.ML"],"title_canon_sha256":"82e264f501ca3404548f760bf0dfec4affd231b2116813d7bdcd5cc3911f8b1a","abstract_canon_sha256":"23eea977be5074415488ffb47dd6f702f2368616b702221571080642c7c21c41"},"schema_version":"1.0"},"canonical_sha256":"d0a37059e2b46a828db2b3910634210caf6a7d707c88c36b7a2fe5fbbead8f97","source":{"kind":"arxiv","id":"2412.19517","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.19517","created_at":"2026-07-05T09:54:37Z"},{"alias_kind":"arxiv_version","alias_value":"2412.19517v1","created_at":"2026-07-05T09:54:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.19517","created_at":"2026-07-05T09:54:37Z"},{"alias_kind":"pith_short_12","alias_value":"2CRXAWPCWRVI","created_at":"2026-07-05T09:54:37Z"},{"alias_kind":"pith_short_16","alias_value":"2CRXAWPCWRVIFDNS","created_at":"2026-07-05T09:54:37Z"},{"alias_kind":"pith_short_8","alias_value":"2CRXAWPC","created_at":"2026-07-05T09:54:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:2CRXAWPCWRVIFDNSWOIQMNBBBS","target":"record","payload":{"canonical_record":{"source":{"id":"2412.19517","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-27T08:19:23Z","cross_cats_sorted":["cs.AI","cs.NA","math.NA","q-bio.PE","stat.ML"],"title_canon_sha256":"82e264f501ca3404548f760bf0dfec4affd231b2116813d7bdcd5cc3911f8b1a","abstract_canon_sha256":"23eea977be5074415488ffb47dd6f702f2368616b702221571080642c7c21c41"},"schema_version":"1.0"},"canonical_sha256":"d0a37059e2b46a828db2b3910634210caf6a7d707c88c36b7a2fe5fbbead8f97","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:54:37.138427Z","signature_b64":"W9iB3haOPICGiPpWM3aNBCpRYz1pr/qqFFuGQdPrq65Ozu89dweIdBLRde1K2HRo3N4KB5YyI67p74c/51sCDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d0a37059e2b46a828db2b3910634210caf6a7d707c88c36b7a2fe5fbbead8f97","last_reissued_at":"2026-07-05T09:54:37.137930Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:54:37.137930Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.19517","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:54:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0vzAjMiJ6kqQsk9T3boVDY453oRcvVmE1S1rI4HLZev5LZ3YFnd2V1MqQiGj/hW2G+fPqHBNqrqGENBb0/FZDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T10:13:43.030883Z"},"content_sha256":"c2af8bee08e7663f6815ed17dc3397ff06d3d0fc447dbe77fef07fc1c27d68e8","schema_version":"1.0","event_id":"sha256:c2af8bee08e7663f6815ed17dc3397ff06d3d0fc447dbe77fef07fc1c27d68e8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:2CRXAWPCWRVIFDNSWOIQMNBBBS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Estimation of System Parameters Including Repeated Cross-Sectional Data through Emulator-Informed Deep Generative Model","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.NA","math.NA","q-bio.PE","stat.ML"],"primary_cat":"cs.LG","authors_text":"Hyeontae Jo, Hyung Ju Hwang, Hyunwoo Cho, Sung Woong Cho","submitted_at":"2024-12-27T08:19:23Z","abstract_excerpt":"Differential equations (DEs) are crucial for modeling the evolution of natural or engineered systems. Traditionally, the parameters in DEs are adjusted to fit data from system observations. However, in fields such as politics, economics, and biology, available data are often independently collected at distinct time points from different subjects (i.e., repeated cross-sectional (RCS) data). Conventional optimization techniques struggle to accurately estimate DE parameters when RCS data exhibit various heterogeneities, leading to a significant loss of information. To address this issue, we propo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.19517","kind":"arxiv","version":1},"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/2412.19517/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":"2026-07-05T09:54:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lRUbnGkpsExDR+/k2B33xReI0mJP0aKtAHlymIDeQSF5rM7Ay9uJ+mwq1rokLC5PI7xgnlzp1zYwnQ5kGzJkAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T10:13:43.031276Z"},"content_sha256":"96a155c31e7d633da1dbd3aef1e715c42d8f44f43f3a0de3ae522618a2879468","schema_version":"1.0","event_id":"sha256:96a155c31e7d633da1dbd3aef1e715c42d8f44f43f3a0de3ae522618a2879468"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2CRXAWPCWRVIFDNSWOIQMNBBBS/bundle.json","state_url":"https://pith.science/pith/2CRXAWPCWRVIFDNSWOIQMNBBBS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2CRXAWPCWRVIFDNSWOIQMNBBBS/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":"2026-08-13T10:13:43Z","links":{"resolver":"https://pith.science/pith/2CRXAWPCWRVIFDNSWOIQMNBBBS","bundle":"https://pith.science/pith/2CRXAWPCWRVIFDNSWOIQMNBBBS/bundle.json","state":"https://pith.science/pith/2CRXAWPCWRVIFDNSWOIQMNBBBS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2CRXAWPCWRVIFDNSWOIQMNBBBS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:2CRXAWPCWRVIFDNSWOIQMNBBBS","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":"23eea977be5074415488ffb47dd6f702f2368616b702221571080642c7c21c41","cross_cats_sorted":["cs.AI","cs.NA","math.NA","q-bio.PE","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-27T08:19:23Z","title_canon_sha256":"82e264f501ca3404548f760bf0dfec4affd231b2116813d7bdcd5cc3911f8b1a"},"schema_version":"1.0","source":{"id":"2412.19517","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.19517","created_at":"2026-07-05T09:54:37Z"},{"alias_kind":"arxiv_version","alias_value":"2412.19517v1","created_at":"2026-07-05T09:54:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.19517","created_at":"2026-07-05T09:54:37Z"},{"alias_kind":"pith_short_12","alias_value":"2CRXAWPCWRVI","created_at":"2026-07-05T09:54:37Z"},{"alias_kind":"pith_short_16","alias_value":"2CRXAWPCWRVIFDNS","created_at":"2026-07-05T09:54:37Z"},{"alias_kind":"pith_short_8","alias_value":"2CRXAWPC","created_at":"2026-07-05T09:54:37Z"}],"graph_snapshots":[{"event_id":"sha256:96a155c31e7d633da1dbd3aef1e715c42d8f44f43f3a0de3ae522618a2879468","target":"graph","created_at":"2026-07-05T09:54:37Z","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/2412.19517/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Differential equations (DEs) are crucial for modeling the evolution of natural or engineered systems. Traditionally, the parameters in DEs are adjusted to fit data from system observations. However, in fields such as politics, economics, and biology, available data are often independently collected at distinct time points from different subjects (i.e., repeated cross-sectional (RCS) data). Conventional optimization techniques struggle to accurately estimate DE parameters when RCS data exhibit various heterogeneities, leading to a significant loss of information. To address this issue, we propo","authors_text":"Hyeontae Jo, Hyung Ju Hwang, Hyunwoo Cho, Sung Woong Cho","cross_cats":["cs.AI","cs.NA","math.NA","q-bio.PE","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-27T08:19:23Z","title":"Estimation of System Parameters Including Repeated Cross-Sectional Data through Emulator-Informed Deep Generative Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.19517","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:c2af8bee08e7663f6815ed17dc3397ff06d3d0fc447dbe77fef07fc1c27d68e8","target":"record","created_at":"2026-07-05T09:54:37Z","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":"23eea977be5074415488ffb47dd6f702f2368616b702221571080642c7c21c41","cross_cats_sorted":["cs.AI","cs.NA","math.NA","q-bio.PE","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-27T08:19:23Z","title_canon_sha256":"82e264f501ca3404548f760bf0dfec4affd231b2116813d7bdcd5cc3911f8b1a"},"schema_version":"1.0","source":{"id":"2412.19517","kind":"arxiv","version":1}},"canonical_sha256":"d0a37059e2b46a828db2b3910634210caf6a7d707c88c36b7a2fe5fbbead8f97","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d0a37059e2b46a828db2b3910634210caf6a7d707c88c36b7a2fe5fbbead8f97","first_computed_at":"2026-07-05T09:54:37.137930Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:54:37.137930Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"W9iB3haOPICGiPpWM3aNBCpRYz1pr/qqFFuGQdPrq65Ozu89dweIdBLRde1K2HRo3N4KB5YyI67p74c/51sCDw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:54:37.138427Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.19517","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c2af8bee08e7663f6815ed17dc3397ff06d3d0fc447dbe77fef07fc1c27d68e8","sha256:96a155c31e7d633da1dbd3aef1e715c42d8f44f43f3a0de3ae522618a2879468"],"state_sha256":"aa86340d30deb7c3b39a831899ee295d8b3fefa56fc8c12e4689bba2da936bdc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"npXBUhg7r7p297Sj8DQPIUSYbFc7c97QxHSiIaCWzhEXwDM3wNlTJmYD15wpSLyzpjGSSry0eQC/ou9B0bejCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T10:13:43.033959Z","bundle_sha256":"47acc6e1b36f15549a818492769bbce106c239d74e7f77b5aeeab6bc838ca42a"}}