{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:N3RZ7KOM6HX4M3JXO76K6EVWCY","short_pith_number":"pith:N3RZ7KOM","canonical_record":{"source":{"id":"1912.09953","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-12-20T17:20:38Z","cross_cats_sorted":["cs.CV","cs.LG","stat.ML"],"title_canon_sha256":"eceeae2e6d32e6a2e2c9a3fc6777e042702c6a152de94b3c5843fd2130dbf6a2","abstract_canon_sha256":"f61147bcc232dabb2edb0ee350787176e8d703d7531d4d81ad4ede39f60c9c8d"},"schema_version":"1.0"},"canonical_sha256":"6ee39fa9ccf1efc66d3777fcaf12b6163428e32033a18832df15d6cfb34ab9a3","source":{"kind":"arxiv","id":"1912.09953","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.09953","created_at":"2026-07-05T00:27:39Z"},{"alias_kind":"arxiv_version","alias_value":"1912.09953v1","created_at":"2026-07-05T00:27:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.09953","created_at":"2026-07-05T00:27:39Z"},{"alias_kind":"pith_short_12","alias_value":"N3RZ7KOM6HX4","created_at":"2026-07-05T00:27:39Z"},{"alias_kind":"pith_short_16","alias_value":"N3RZ7KOM6HX4M3JX","created_at":"2026-07-05T00:27:39Z"},{"alias_kind":"pith_short_8","alias_value":"N3RZ7KOM","created_at":"2026-07-05T00:27:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:N3RZ7KOM6HX4M3JXO76K6EVWCY","target":"record","payload":{"canonical_record":{"source":{"id":"1912.09953","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-12-20T17:20:38Z","cross_cats_sorted":["cs.CV","cs.LG","stat.ML"],"title_canon_sha256":"eceeae2e6d32e6a2e2c9a3fc6777e042702c6a152de94b3c5843fd2130dbf6a2","abstract_canon_sha256":"f61147bcc232dabb2edb0ee350787176e8d703d7531d4d81ad4ede39f60c9c8d"},"schema_version":"1.0"},"canonical_sha256":"6ee39fa9ccf1efc66d3777fcaf12b6163428e32033a18832df15d6cfb34ab9a3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:27:39.612918Z","signature_b64":"5h/9UfVh1qnEEQkCYFFyQTXgNybOZZIwU/Hz/KmNvnftMewCp5yKIFZ56C6hv14p5fqUdE8znss96uIMJtQODA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6ee39fa9ccf1efc66d3777fcaf12b6163428e32033a18832df15d6cfb34ab9a3","last_reissued_at":"2026-07-05T00:27:39.612553Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:27:39.612553Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1912.09953","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":"2026-07-05T00:27:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PeuwF8xKAcUQtil7P5rOaDVWzOAg/qBV63r2L8K4dLhcMHZgKHWIpaci9xk4GJPIublfCQLxqfeMhVaMsNnRAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T14:06:08.375106Z"},"content_sha256":"505b7fe5694e0b06eb86fab8b9b312bf4b733511d39483abd54c1d9b2ecb87ed","schema_version":"1.0","event_id":"sha256:505b7fe5694e0b06eb86fab8b9b312bf4b733511d39483abd54c1d9b2ecb87ed"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:N3RZ7KOM6HX4M3JXO76K6EVWCY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"HiLLoC: Lossless Image Compression with Hierarchical Latent Variable Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.LG","stat.ML"],"primary_cat":"eess.IV","authors_text":"David Barber, James Townsend, Julius Kunze, Thomas Bird","submitted_at":"2019-12-20T17:20:38Z","abstract_excerpt":"We make the following striking observation: fully convolutional VAE models trained on 32x32 ImageNet can generalize well, not just to 64x64 but also to far larger photographs, with no changes to the model. We use this property, applying fully convolutional models to lossless compression, demonstrating a method to scale the VAE-based 'Bits-Back with ANS' algorithm for lossless compression to large color photographs, and achieving state of the art for compression of full size ImageNet images. We release Craystack, an open source library for convenient prototyping of lossless compression using pr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.09953","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/1912.09953/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":"2026-07-05T00:27:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3wjCDBMmGkmPB0vdJ27M9oM+DswUFz/C7NkfYoYwFejXzomkU+QWbxt0T1gwN+l1ddbaiK/PDD/ATla4BAJTAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T14:06:08.375628Z"},"content_sha256":"b2a32afad9bf75eb8df6977efda4b9b8ac1b78e64f9a71ab24ad16755c0910d5","schema_version":"1.0","event_id":"sha256:b2a32afad9bf75eb8df6977efda4b9b8ac1b78e64f9a71ab24ad16755c0910d5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N3RZ7KOM6HX4M3JXO76K6EVWCY/bundle.json","state_url":"https://pith.science/pith/N3RZ7KOM6HX4M3JXO76K6EVWCY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N3RZ7KOM6HX4M3JXO76K6EVWCY/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":"2026-08-18T14:06:08Z","links":{"resolver":"https://pith.science/pith/N3RZ7KOM6HX4M3JXO76K6EVWCY","bundle":"https://pith.science/pith/N3RZ7KOM6HX4M3JXO76K6EVWCY/bundle.json","state":"https://pith.science/pith/N3RZ7KOM6HX4M3JXO76K6EVWCY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N3RZ7KOM6HX4M3JXO76K6EVWCY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:N3RZ7KOM6HX4M3JXO76K6EVWCY","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":"f61147bcc232dabb2edb0ee350787176e8d703d7531d4d81ad4ede39f60c9c8d","cross_cats_sorted":["cs.CV","cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-12-20T17:20:38Z","title_canon_sha256":"eceeae2e6d32e6a2e2c9a3fc6777e042702c6a152de94b3c5843fd2130dbf6a2"},"schema_version":"1.0","source":{"id":"1912.09953","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.09953","created_at":"2026-07-05T00:27:39Z"},{"alias_kind":"arxiv_version","alias_value":"1912.09953v1","created_at":"2026-07-05T00:27:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.09953","created_at":"2026-07-05T00:27:39Z"},{"alias_kind":"pith_short_12","alias_value":"N3RZ7KOM6HX4","created_at":"2026-07-05T00:27:39Z"},{"alias_kind":"pith_short_16","alias_value":"N3RZ7KOM6HX4M3JX","created_at":"2026-07-05T00:27:39Z"},{"alias_kind":"pith_short_8","alias_value":"N3RZ7KOM","created_at":"2026-07-05T00:27:39Z"}],"graph_snapshots":[{"event_id":"sha256:b2a32afad9bf75eb8df6977efda4b9b8ac1b78e64f9a71ab24ad16755c0910d5","target":"graph","created_at":"2026-07-05T00:27:39Z","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/1912.09953/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We make the following striking observation: fully convolutional VAE models trained on 32x32 ImageNet can generalize well, not just to 64x64 but also to far larger photographs, with no changes to the model. We use this property, applying fully convolutional models to lossless compression, demonstrating a method to scale the VAE-based 'Bits-Back with ANS' algorithm for lossless compression to large color photographs, and achieving state of the art for compression of full size ImageNet images. We release Craystack, an open source library for convenient prototyping of lossless compression using pr","authors_text":"David Barber, James Townsend, Julius Kunze, Thomas Bird","cross_cats":["cs.CV","cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-12-20T17:20:38Z","title":"HiLLoC: Lossless Image Compression with Hierarchical Latent Variable Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.09953","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":"sha256:505b7fe5694e0b06eb86fab8b9b312bf4b733511d39483abd54c1d9b2ecb87ed","target":"record","created_at":"2026-07-05T00:27:39Z","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":"f61147bcc232dabb2edb0ee350787176e8d703d7531d4d81ad4ede39f60c9c8d","cross_cats_sorted":["cs.CV","cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-12-20T17:20:38Z","title_canon_sha256":"eceeae2e6d32e6a2e2c9a3fc6777e042702c6a152de94b3c5843fd2130dbf6a2"},"schema_version":"1.0","source":{"id":"1912.09953","kind":"arxiv","version":1}},"canonical_sha256":"6ee39fa9ccf1efc66d3777fcaf12b6163428e32033a18832df15d6cfb34ab9a3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6ee39fa9ccf1efc66d3777fcaf12b6163428e32033a18832df15d6cfb34ab9a3","first_computed_at":"2026-07-05T00:27:39.612553Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:27:39.612553Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5h/9UfVh1qnEEQkCYFFyQTXgNybOZZIwU/Hz/KmNvnftMewCp5yKIFZ56C6hv14p5fqUdE8znss96uIMJtQODA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:27:39.612918Z","signed_message":"canonical_sha256_bytes"},"source_id":"1912.09953","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:505b7fe5694e0b06eb86fab8b9b312bf4b733511d39483abd54c1d9b2ecb87ed","sha256:b2a32afad9bf75eb8df6977efda4b9b8ac1b78e64f9a71ab24ad16755c0910d5"],"state_sha256":"d22f5d8e9c86bffd63d460b997490ced72e8f00b12e62a3e069eb79e1f36036a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y7jiRpRT5y/Sc9huAU+fe5b1uJlsKHPujCO3EFcDiKSchm2mO7wuazITxk8EZ1PAnC54m1HReuyXyCK0/BA5BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T14:06:08.379452Z","bundle_sha256":"39327ac4188f47de3495effea2b3043bc85428d591d5a3d38395303bc11d6258"}}