{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:ZLI4J3TZZAYGFCNNKSGOWEZJU5","short_pith_number":"pith:ZLI4J3TZ","canonical_record":{"source":{"id":"1808.04745","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-14T15:24:39Z","cross_cats_sorted":[],"title_canon_sha256":"5eafc010b9def22e4d0c6e3d3dba0adc8cb26a59d4371bb18ff41c158d6381ef","abstract_canon_sha256":"7d9479aca28470cb6634ab38494698955dbfaa66be42889dcc9cba2341f0560a"},"schema_version":"1.0"},"canonical_sha256":"cad1c4ee79c8306289ad548ceb1329a74de7f5e856adfabe51d6fc1d1092380f","source":{"kind":"arxiv","id":"1808.04745","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.04745","created_at":"2026-05-18T00:08:11Z"},{"alias_kind":"arxiv_version","alias_value":"1808.04745v1","created_at":"2026-05-18T00:08:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.04745","created_at":"2026-05-18T00:08:11Z"},{"alias_kind":"pith_short_12","alias_value":"ZLI4J3TZZAYG","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"ZLI4J3TZZAYGFCNN","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"ZLI4J3TZ","created_at":"2026-05-18T12:33:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:ZLI4J3TZZAYGFCNNKSGOWEZJU5","target":"record","payload":{"canonical_record":{"source":{"id":"1808.04745","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-14T15:24:39Z","cross_cats_sorted":[],"title_canon_sha256":"5eafc010b9def22e4d0c6e3d3dba0adc8cb26a59d4371bb18ff41c158d6381ef","abstract_canon_sha256":"7d9479aca28470cb6634ab38494698955dbfaa66be42889dcc9cba2341f0560a"},"schema_version":"1.0"},"canonical_sha256":"cad1c4ee79c8306289ad548ceb1329a74de7f5e856adfabe51d6fc1d1092380f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:08:11.797182Z","signature_b64":"QVMHPa+9gY6x+ZfHSRTvezLO/E4jwsFESIcj/S6Gx3xs1285mAg4aF9kiniJH4RQUGnOOOc/j+wkSpvlTN70Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cad1c4ee79c8306289ad548ceb1329a74de7f5e856adfabe51d6fc1d1092380f","last_reissued_at":"2026-05-18T00:08:11.796786Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:08:11.796786Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.04745","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":"2026-05-18T00:08:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"97broqkGSDy9jUa5UgbA+jcE3VBR0yVKPKPahlA5zw0oOv4jwPAfPinkNe/lQb1bDOhg8CKVzHCX0YhJ+hHYCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T11:54:42.164844Z"},"content_sha256":"3fb3d70b234b86d76bbd9f023fe737051a5a6ac7acd80c5800eef95b9b14b004","schema_version":"1.0","event_id":"sha256:3fb3d70b234b86d76bbd9f023fe737051a5a6ac7acd80c5800eef95b9b14b004"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:ZLI4J3TZZAYGFCNNKSGOWEZJU5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Imagining the Unseen: Learning a Distribution over Incomplete Images with Dense Latent Trees","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Andrew Blake, John Redford, Sebastian Kaltwang, Sina Samangooei","submitted_at":"2018-08-14T15:24:39Z","abstract_excerpt":"Images are composed as a hierarchy of object parts. We use this insight to create a generative graphical model that defines a hierarchical distribution over image parts. Typically, this leads to intractable inference due to loops in the graph. We propose an alternative model structure, the Dense Latent Tree (DLT), which avoids loops and allows for efficient exact inference, while maintaining a dense connectivity between parts of the hierarchy. The usefulness of DLTs is shown for the example task of image completion on partially observed MNIST and Fashion-MNIST data. We verify having successful"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.04745","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":""},"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":"2026-05-18T00:08:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O+Omodxwax/8kCrDafobMa6pWqkNLabxtPGaYGs8qxXXSJT5hELzfR12DOKJPItPw0YClCQlSDfBbiRWux8wCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T11:54:42.165188Z"},"content_sha256":"075249a431d9c91c1e529d99cd05c5cca14651f0f0ac20c29a0717422c754e8c","schema_version":"1.0","event_id":"sha256:075249a431d9c91c1e529d99cd05c5cca14651f0f0ac20c29a0717422c754e8c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZLI4J3TZZAYGFCNNKSGOWEZJU5/bundle.json","state_url":"https://pith.science/pith/ZLI4J3TZZAYGFCNNKSGOWEZJU5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZLI4J3TZZAYGFCNNKSGOWEZJU5/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":"2026-06-26T11:54:42Z","links":{"resolver":"https://pith.science/pith/ZLI4J3TZZAYGFCNNKSGOWEZJU5","bundle":"https://pith.science/pith/ZLI4J3TZZAYGFCNNKSGOWEZJU5/bundle.json","state":"https://pith.science/pith/ZLI4J3TZZAYGFCNNKSGOWEZJU5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZLI4J3TZZAYGFCNNKSGOWEZJU5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:ZLI4J3TZZAYGFCNNKSGOWEZJU5","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":"7d9479aca28470cb6634ab38494698955dbfaa66be42889dcc9cba2341f0560a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-14T15:24:39Z","title_canon_sha256":"5eafc010b9def22e4d0c6e3d3dba0adc8cb26a59d4371bb18ff41c158d6381ef"},"schema_version":"1.0","source":{"id":"1808.04745","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.04745","created_at":"2026-05-18T00:08:11Z"},{"alias_kind":"arxiv_version","alias_value":"1808.04745v1","created_at":"2026-05-18T00:08:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.04745","created_at":"2026-05-18T00:08:11Z"},{"alias_kind":"pith_short_12","alias_value":"ZLI4J3TZZAYG","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"ZLI4J3TZZAYGFCNN","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"ZLI4J3TZ","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:075249a431d9c91c1e529d99cd05c5cca14651f0f0ac20c29a0717422c754e8c","target":"graph","created_at":"2026-05-18T00:08:11Z","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":"Images are composed as a hierarchy of object parts. We use this insight to create a generative graphical model that defines a hierarchical distribution over image parts. Typically, this leads to intractable inference due to loops in the graph. We propose an alternative model structure, the Dense Latent Tree (DLT), which avoids loops and allows for efficient exact inference, while maintaining a dense connectivity between parts of the hierarchy. The usefulness of DLTs is shown for the example task of image completion on partially observed MNIST and Fashion-MNIST data. We verify having successful","authors_text":"Andrew Blake, John Redford, Sebastian Kaltwang, Sina Samangooei","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-14T15:24:39Z","title":"Imagining the Unseen: Learning a Distribution over Incomplete Images with Dense Latent Trees"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.04745","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":"sha256:3fb3d70b234b86d76bbd9f023fe737051a5a6ac7acd80c5800eef95b9b14b004","target":"record","created_at":"2026-05-18T00:08:11Z","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":"7d9479aca28470cb6634ab38494698955dbfaa66be42889dcc9cba2341f0560a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-14T15:24:39Z","title_canon_sha256":"5eafc010b9def22e4d0c6e3d3dba0adc8cb26a59d4371bb18ff41c158d6381ef"},"schema_version":"1.0","source":{"id":"1808.04745","kind":"arxiv","version":1}},"canonical_sha256":"cad1c4ee79c8306289ad548ceb1329a74de7f5e856adfabe51d6fc1d1092380f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cad1c4ee79c8306289ad548ceb1329a74de7f5e856adfabe51d6fc1d1092380f","first_computed_at":"2026-05-18T00:08:11.796786Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:08:11.796786Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QVMHPa+9gY6x+ZfHSRTvezLO/E4jwsFESIcj/S6Gx3xs1285mAg4aF9kiniJH4RQUGnOOOc/j+wkSpvlTN70Cg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:08:11.797182Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.04745","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3fb3d70b234b86d76bbd9f023fe737051a5a6ac7acd80c5800eef95b9b14b004","sha256:075249a431d9c91c1e529d99cd05c5cca14651f0f0ac20c29a0717422c754e8c"],"state_sha256":"84965dce999a88601893f61e1ffedd82fbf32eec129fda730efe05c6c579723e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m2NRC9tJAZD9XDu7Swi73FjNXNLdC88hBaT1WsJ6uIaTKZtNkjCFFefc+O0/wJ3tNZzCo1Wk9un3LrdLYvvYDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-26T11:54:42.167160Z","bundle_sha256":"a3b53d0ab22eb5eefce68a4977639f6d58db583599471340da7c50cd98acdd3e"}}