{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:YHTGRNXZAVNSIA5FRTTHAB454B","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":"6f10276e6b26b29bfd4cecb3c236a338f944c939ca6ce8db3ffcb8666825c6a4","cross_cats_sorted":["stat.ME","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2019-05-31T18:52:21Z","title_canon_sha256":"0869db54e2ce7290397a91038449e657890327e6e53277f39d32b1adc7866262"},"schema_version":"1.0","source":{"id":"1906.00031","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.00031","created_at":"2026-07-05T01:54:40Z"},{"alias_kind":"arxiv_version","alias_value":"1906.00031v3","created_at":"2026-07-05T01:54:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.00031","created_at":"2026-07-05T01:54:40Z"},{"alias_kind":"pith_short_12","alias_value":"YHTGRNXZAVNS","created_at":"2026-07-05T01:54:40Z"},{"alias_kind":"pith_short_16","alias_value":"YHTGRNXZAVNSIA5F","created_at":"2026-07-05T01:54:40Z"},{"alias_kind":"pith_short_8","alias_value":"YHTGRNXZ","created_at":"2026-07-05T01:54:40Z"}],"graph_snapshots":[{"event_id":"sha256:91b90ee89a2b96a0eb778a923c51e0c24c01a5fbd68f1e44bd62ee30c52745af","target":"graph","created_at":"2026-07-05T01:54:40Z","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/1906.00031/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose a framework for solving high-dimensional Bayesian inference problems using \\emph{structure-exploiting} low-dimensional transport maps or flows. These maps are confined to a low-dimensional subspace (hence, lazy), and the subspace is identified by minimizing an upper bound on the Kullback--Leibler divergence (hence, structured). Our framework provides a principled way of identifying and exploiting low-dimensional structure in an inference problem. It focuses the expressiveness of a transport map along the directions of most significant discrepancy from the posterior, and can be used ","authors_text":"Alessio Spantini, Daniele Bigoni, Michael C. Brennan, Olivier Zahm, Youssef Marzouk","cross_cats":["stat.ME","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2019-05-31T18:52:21Z","title":"Greedy inference with structure-exploiting lazy maps"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.00031","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":"sha256:73ec40ffcc109339eaaecb01ab9bd5203f15cc104ec0e8310747e963c6da22cc","target":"record","created_at":"2026-07-05T01:54:40Z","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":"6f10276e6b26b29bfd4cecb3c236a338f944c939ca6ce8db3ffcb8666825c6a4","cross_cats_sorted":["stat.ME","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2019-05-31T18:52:21Z","title_canon_sha256":"0869db54e2ce7290397a91038449e657890327e6e53277f39d32b1adc7866262"},"schema_version":"1.0","source":{"id":"1906.00031","kind":"arxiv","version":3}},"canonical_sha256":"c1e668b6f9055b2403a58ce670079de058fbe5cc2fe7183137aa39dd49937fb2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c1e668b6f9055b2403a58ce670079de058fbe5cc2fe7183137aa39dd49937fb2","first_computed_at":"2026-07-05T01:54:40.684896Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:54:40.684896Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NKfYixNaMiOLY8+usbLmMtkwE6vr+hV6qTJlpEqf54DnhlqSe486TbFA1MENl+oSvxvqaTt7694RqWki0i9vDw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:54:40.685460Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.00031","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:73ec40ffcc109339eaaecb01ab9bd5203f15cc104ec0e8310747e963c6da22cc","sha256:91b90ee89a2b96a0eb778a923c51e0c24c01a5fbd68f1e44bd62ee30c52745af"],"state_sha256":"7dea87d7d7302f58454a50f88affc61de73fb005a9468c22168d8b5e723b39ea"}