{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:FBNQTVA27DEMYIALTAW2U53ROJ","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":"f7b52675c46752cd78f8c6da3fbaba6000dc679f852a7cdd6b0c16e873286fc7","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-11T20:39:29Z","title_canon_sha256":"e9afb7a916e83ca7096b31d3980581c1e2c79935b56c903422bc302a3c3fbe30"},"schema_version":"1.0","source":{"id":"1904.05948","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.05948","created_at":"2026-05-17T23:40:48Z"},{"alias_kind":"arxiv_version","alias_value":"1904.05948v2","created_at":"2026-05-17T23:40:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.05948","created_at":"2026-05-17T23:40:48Z"},{"alias_kind":"pith_short_12","alias_value":"FBNQTVA27DEM","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"FBNQTVA27DEMYIAL","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"FBNQTVA2","created_at":"2026-05-18T12:33:15Z"}],"graph_snapshots":[{"event_id":"sha256:86b0adea4d852df6c9d44462e15c2c7a6e7e5ca99ad84ecef2488b3ca5183be8","target":"graph","created_at":"2026-05-17T23:40:48Z","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"},"paper":{"abstract_excerpt":"While unsupervised variational autoencoders (VAE) have become a powerful tool in neuroimage analysis, their application to supervised learning is under-explored. We aim to close this gap by proposing a unified probabilistic model for learning the latent space of imaging data and performing supervised regression. Based on recent advances in learning disentangled representations, the novel generative process explicitly models the conditional distribution of latent representations with respect to the regression target variable. Performing a variational inference procedure on this model leads to j","authors_text":"Ehsan Adeli, Kilian M. Pohl, Nicolas Honnorat, Qingyu Zhao, Tuo Leng","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-11T20:39:29Z","title":"Variational AutoEncoder For Regression: Application to Brain Aging Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.05948","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:f259851569f633ae5039152dbc23b2f6e7d58384a0b77c4239cb3624ceefde96","target":"record","created_at":"2026-05-17T23:40:48Z","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":"f7b52675c46752cd78f8c6da3fbaba6000dc679f852a7cdd6b0c16e873286fc7","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-11T20:39:29Z","title_canon_sha256":"e9afb7a916e83ca7096b31d3980581c1e2c79935b56c903422bc302a3c3fbe30"},"schema_version":"1.0","source":{"id":"1904.05948","kind":"arxiv","version":2}},"canonical_sha256":"285b09d41af8c8cc200b982daa77717274f85ef65bc5759d9b6d2ddb819c240d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"285b09d41af8c8cc200b982daa77717274f85ef65bc5759d9b6d2ddb819c240d","first_computed_at":"2026-05-17T23:40:48.951737Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:40:48.951737Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"q+NBRsMC78L8KiMaJEgAWGSOyKnorue0meGn320dS8rBePgaJ7Nihx0DR5LmHOvjp67OZqA24ms9W2HbrPEfDg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:40:48.952498Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.05948","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f259851569f633ae5039152dbc23b2f6e7d58384a0b77c4239cb3624ceefde96","sha256:86b0adea4d852df6c9d44462e15c2c7a6e7e5ca99ad84ecef2488b3ca5183be8"],"state_sha256":"877d0642534a4ae354644b459ccd750a7dfcca80f47b615b7776831bde255123"}