{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:MEM2K4LTPUPVTBP36UOHTBTO2K","short_pith_number":"pith:MEM2K4LT","canonical_record":{"source":{"id":"2605.30625","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-28T22:22:35Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"1dbc2e2fddf7e8ec5a2a2538b49b33344bbcf15d9195c7e7574b16544991cf8b","abstract_canon_sha256":"2bf16e020c2e06894d3a2658d2dcc4007fb88730821d4280e6a2cb27b5632275"},"schema_version":"1.0"},"canonical_sha256":"6119a571737d1f5985fbf51c79866ed2a8586102702bf265747c23bce2732d56","source":{"kind":"arxiv","id":"2605.30625","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30625","created_at":"2026-06-01T01:03:04Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30625v1","created_at":"2026-06-01T01:03:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30625","created_at":"2026-06-01T01:03:04Z"},{"alias_kind":"pith_short_12","alias_value":"MEM2K4LTPUPV","created_at":"2026-06-01T01:03:04Z"},{"alias_kind":"pith_short_16","alias_value":"MEM2K4LTPUPVTBP3","created_at":"2026-06-01T01:03:04Z"},{"alias_kind":"pith_short_8","alias_value":"MEM2K4LT","created_at":"2026-06-01T01:03:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:MEM2K4LTPUPVTBP36UOHTBTO2K","target":"record","payload":{"canonical_record":{"source":{"id":"2605.30625","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-28T22:22:35Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"1dbc2e2fddf7e8ec5a2a2538b49b33344bbcf15d9195c7e7574b16544991cf8b","abstract_canon_sha256":"2bf16e020c2e06894d3a2658d2dcc4007fb88730821d4280e6a2cb27b5632275"},"schema_version":"1.0"},"canonical_sha256":"6119a571737d1f5985fbf51c79866ed2a8586102702bf265747c23bce2732d56","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-01T01:03:04.771886Z","signature_b64":"J97nPdBsvdno0IFIh3beUMwntudskG9cYCa4GottAhfpG6vUfwjbZnHIIz/ksM0J4Dht0eL/kHd9CMkagmB+AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6119a571737d1f5985fbf51c79866ed2a8586102702bf265747c23bce2732d56","last_reissued_at":"2026-06-01T01:03:04.771026Z","signature_status":"signed_v1","first_computed_at":"2026-06-01T01:03:04.771026Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.30625","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":"2026-06-01T01:03:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YrIUJgoeIyzFDZYc+bSxkZdJ0kLPytCXUQvZz9q2z2aEmHHku+tSSUPjopm5Xz4Sc8zAkQ2Fo8TO/5hc0NnaDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T09:16:03.353138Z"},"content_sha256":"3be0a344774e3070f2625b83327d2dd2b653b5bb50ac1534e5b1315ece7f0e38","schema_version":"1.0","event_id":"sha256:3be0a344774e3070f2625b83327d2dd2b653b5bb50ac1534e5b1315ece7f0e38"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:MEM2K4LTPUPVTBP36UOHTBTO2K","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Active Timepoint Selection for Learning Measure-Valued Trajectories","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Mihaela van der Schaar, Nicolas Huynh","submitted_at":"2026-05-28T22:22:35Z","abstract_excerpt":"Inferring continuous probability paths from sparse snapshots is a fundamental challenge in domains like single-cell biology, where high-fidelity data acquisition is often destructive and constrained by prohibitive sequencing costs. This motivates the need for active learning strategies to strategically select optimal measurement times. However, designing active learning policies for this setting remains an open problem: the target objects reside on the infinite dimensional Wasserstein space where standard Euclidean metrics are ill-defined, and current interpolation methods lack epistemic uncer"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30625","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/2605.30625/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":"2026-06-01T01:03:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zuCgRgV5Oj4aEiAuL6iTUJdh8EHZPatgDk/KHc0VMCRgy8zMxbfLxGNQ8mnUOT+XahuskWowLnmuCvORrlXgAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T09:16:03.353849Z"},"content_sha256":"e4db128cacec087562fe80fb36f172af8713b1f4d2c6a13cbd68c58c4ea2001b","schema_version":"1.0","event_id":"sha256:e4db128cacec087562fe80fb36f172af8713b1f4d2c6a13cbd68c58c4ea2001b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MEM2K4LTPUPVTBP36UOHTBTO2K/bundle.json","state_url":"https://pith.science/pith/MEM2K4LTPUPVTBP36UOHTBTO2K/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MEM2K4LTPUPVTBP36UOHTBTO2K/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":"2026-06-07T09:16:03Z","links":{"resolver":"https://pith.science/pith/MEM2K4LTPUPVTBP36UOHTBTO2K","bundle":"https://pith.science/pith/MEM2K4LTPUPVTBP36UOHTBTO2K/bundle.json","state":"https://pith.science/pith/MEM2K4LTPUPVTBP36UOHTBTO2K/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MEM2K4LTPUPVTBP36UOHTBTO2K/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:MEM2K4LTPUPVTBP36UOHTBTO2K","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":"2bf16e020c2e06894d3a2658d2dcc4007fb88730821d4280e6a2cb27b5632275","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-28T22:22:35Z","title_canon_sha256":"1dbc2e2fddf7e8ec5a2a2538b49b33344bbcf15d9195c7e7574b16544991cf8b"},"schema_version":"1.0","source":{"id":"2605.30625","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30625","created_at":"2026-06-01T01:03:04Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30625v1","created_at":"2026-06-01T01:03:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30625","created_at":"2026-06-01T01:03:04Z"},{"alias_kind":"pith_short_12","alias_value":"MEM2K4LTPUPV","created_at":"2026-06-01T01:03:04Z"},{"alias_kind":"pith_short_16","alias_value":"MEM2K4LTPUPVTBP3","created_at":"2026-06-01T01:03:04Z"},{"alias_kind":"pith_short_8","alias_value":"MEM2K4LT","created_at":"2026-06-01T01:03:04Z"}],"graph_snapshots":[{"event_id":"sha256:e4db128cacec087562fe80fb36f172af8713b1f4d2c6a13cbd68c58c4ea2001b","target":"graph","created_at":"2026-06-01T01:03:04Z","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/2605.30625/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Inferring continuous probability paths from sparse snapshots is a fundamental challenge in domains like single-cell biology, where high-fidelity data acquisition is often destructive and constrained by prohibitive sequencing costs. This motivates the need for active learning strategies to strategically select optimal measurement times. However, designing active learning policies for this setting remains an open problem: the target objects reside on the infinite dimensional Wasserstein space where standard Euclidean metrics are ill-defined, and current interpolation methods lack epistemic uncer","authors_text":"Mihaela van der Schaar, Nicolas Huynh","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-28T22:22:35Z","title":"Active Timepoint Selection for Learning Measure-Valued Trajectories"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30625","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":"sha256:3be0a344774e3070f2625b83327d2dd2b653b5bb50ac1534e5b1315ece7f0e38","target":"record","created_at":"2026-06-01T01:03:04Z","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":"2bf16e020c2e06894d3a2658d2dcc4007fb88730821d4280e6a2cb27b5632275","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-28T22:22:35Z","title_canon_sha256":"1dbc2e2fddf7e8ec5a2a2538b49b33344bbcf15d9195c7e7574b16544991cf8b"},"schema_version":"1.0","source":{"id":"2605.30625","kind":"arxiv","version":1}},"canonical_sha256":"6119a571737d1f5985fbf51c79866ed2a8586102702bf265747c23bce2732d56","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6119a571737d1f5985fbf51c79866ed2a8586102702bf265747c23bce2732d56","first_computed_at":"2026-06-01T01:03:04.771026Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-01T01:03:04.771026Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"J97nPdBsvdno0IFIh3beUMwntudskG9cYCa4GottAhfpG6vUfwjbZnHIIz/ksM0J4Dht0eL/kHd9CMkagmB+AA==","signature_status":"signed_v1","signed_at":"2026-06-01T01:03:04.771886Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.30625","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3be0a344774e3070f2625b83327d2dd2b653b5bb50ac1534e5b1315ece7f0e38","sha256:e4db128cacec087562fe80fb36f172af8713b1f4d2c6a13cbd68c58c4ea2001b"],"state_sha256":"f399d524c7a0a9bb110caf42fcb0ce40ca75d3ae1c2bd492903b7b2b32dbadf2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Bh8qitSE9Z6ogS1r60SAay3JG5bxZOsQ6nt3bzuXFuEy9GzU+GY0sPVAOLW1MKnv9NmV7g6Co+DeUhMh6f3xBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T09:16:03.357377Z","bundle_sha256":"b4325dfbab6a360bb4f9e65607154f38803ec8e4457c48eb82fbbeb82841d1ca"}}