{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:SUMVL234DN5LKU45D6A6T5KJ55","short_pith_number":"pith:SUMVL234","canonical_record":{"source":{"id":"1706.00531","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-02T00:53:14Z","cross_cats_sorted":[],"title_canon_sha256":"530690ecfd3319a7e120a0484fdaf563af34a9355a75900339e0517c8a33ff5a","abstract_canon_sha256":"f141771d9191a4fea3a8637f0358e1f25ecb305295038e11ea917f2790d1ee5b"},"schema_version":"1.0"},"canonical_sha256":"951955eb7c1b7ab5539d1f81e9f549ef66cc9c66b7390b06105217822d8eddea","source":{"kind":"arxiv","id":"1706.00531","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.00531","created_at":"2026-05-18T00:43:12Z"},{"alias_kind":"arxiv_version","alias_value":"1706.00531v1","created_at":"2026-05-18T00:43:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.00531","created_at":"2026-05-18T00:43:12Z"},{"alias_kind":"pith_short_12","alias_value":"SUMVL234DN5L","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"SUMVL234DN5LKU45","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"SUMVL234","created_at":"2026-05-18T12:31:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:SUMVL234DN5LKU45D6A6T5KJ55","target":"record","payload":{"canonical_record":{"source":{"id":"1706.00531","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-02T00:53:14Z","cross_cats_sorted":[],"title_canon_sha256":"530690ecfd3319a7e120a0484fdaf563af34a9355a75900339e0517c8a33ff5a","abstract_canon_sha256":"f141771d9191a4fea3a8637f0358e1f25ecb305295038e11ea917f2790d1ee5b"},"schema_version":"1.0"},"canonical_sha256":"951955eb7c1b7ab5539d1f81e9f549ef66cc9c66b7390b06105217822d8eddea","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:43:12.762758Z","signature_b64":"vFWPHyEhWblOvDR98+e4cXgcAzlJnvgA+0+7S2jMx4xXYgAxTWhx3Tj56Dz6lNfEq1fjBIl+fz9KDF09OA44BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"951955eb7c1b7ab5539d1f81e9f549ef66cc9c66b7390b06105217822d8eddea","last_reissued_at":"2026-05-18T00:43:12.762082Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:43:12.762082Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1706.00531","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":"2026-05-18T00:43:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jiDpYHS+6/Tx2Fo6kmbTukzQuoBLd3UInxxO1hEhhrJzv2GizyRUjUV9GDQtr3lDOqo7dzQgz5WwU+Hd8E0cBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T23:48:38.205550Z"},"content_sha256":"84409a6e0c6899833ee8ddfbea9e52e0ec07c1305c1d416e65218b33185f3e9b","schema_version":"1.0","event_id":"sha256:84409a6e0c6899833ee8ddfbea9e52e0ec07c1305c1d416e65218b33185f3e9b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:SUMVL234DN5LKU45D6A6T5KJ55","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PixelGAN Autoencoders","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Alireza Makhzani, Brendan Frey","submitted_at":"2017-06-02T00:53:14Z","abstract_excerpt":"In this paper, we describe the \"PixelGAN autoencoder\", a generative autoencoder in which the generative path is a convolutional autoregressive neural network on pixels (PixelCNN) that is conditioned on a latent code, and the recognition path uses a generative adversarial network (GAN) to impose a prior distribution on the latent code. We show that different priors result in different decompositions of information between the latent code and the autoregressive decoder. For example, by imposing a Gaussian distribution as the prior, we can achieve a global vs. local decomposition, or by imposing "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.00531","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":"2026-05-18T00:43:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FuV1UQ+iXAooDu/72g94Bb3P2S9Skvr/twTi6apRRO2z8FN1t0a6W7RMAkVu3knRLgGC+kcey+ZtAkApzNdzCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T23:48:38.206069Z"},"content_sha256":"c043fa7aa0cdb8c4f698f0f5c9466a3470438f2dfe0ef141f526364178476622","schema_version":"1.0","event_id":"sha256:c043fa7aa0cdb8c4f698f0f5c9466a3470438f2dfe0ef141f526364178476622"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SUMVL234DN5LKU45D6A6T5KJ55/bundle.json","state_url":"https://pith.science/pith/SUMVL234DN5LKU45D6A6T5KJ55/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SUMVL234DN5LKU45D6A6T5KJ55/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":"2026-05-26T23:48:38Z","links":{"resolver":"https://pith.science/pith/SUMVL234DN5LKU45D6A6T5KJ55","bundle":"https://pith.science/pith/SUMVL234DN5LKU45D6A6T5KJ55/bundle.json","state":"https://pith.science/pith/SUMVL234DN5LKU45D6A6T5KJ55/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SUMVL234DN5LKU45D6A6T5KJ55/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:SUMVL234DN5LKU45D6A6T5KJ55","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":"f141771d9191a4fea3a8637f0358e1f25ecb305295038e11ea917f2790d1ee5b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-02T00:53:14Z","title_canon_sha256":"530690ecfd3319a7e120a0484fdaf563af34a9355a75900339e0517c8a33ff5a"},"schema_version":"1.0","source":{"id":"1706.00531","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.00531","created_at":"2026-05-18T00:43:12Z"},{"alias_kind":"arxiv_version","alias_value":"1706.00531v1","created_at":"2026-05-18T00:43:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.00531","created_at":"2026-05-18T00:43:12Z"},{"alias_kind":"pith_short_12","alias_value":"SUMVL234DN5L","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"SUMVL234DN5LKU45","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"SUMVL234","created_at":"2026-05-18T12:31:43Z"}],"graph_snapshots":[{"event_id":"sha256:c043fa7aa0cdb8c4f698f0f5c9466a3470438f2dfe0ef141f526364178476622","target":"graph","created_at":"2026-05-18T00:43:12Z","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":"In this paper, we describe the \"PixelGAN autoencoder\", a generative autoencoder in which the generative path is a convolutional autoregressive neural network on pixels (PixelCNN) that is conditioned on a latent code, and the recognition path uses a generative adversarial network (GAN) to impose a prior distribution on the latent code. We show that different priors result in different decompositions of information between the latent code and the autoregressive decoder. For example, by imposing a Gaussian distribution as the prior, we can achieve a global vs. local decomposition, or by imposing ","authors_text":"Alireza Makhzani, Brendan Frey","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-02T00:53:14Z","title":"PixelGAN Autoencoders"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.00531","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":"sha256:84409a6e0c6899833ee8ddfbea9e52e0ec07c1305c1d416e65218b33185f3e9b","target":"record","created_at":"2026-05-18T00:43:12Z","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":"f141771d9191a4fea3a8637f0358e1f25ecb305295038e11ea917f2790d1ee5b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-02T00:53:14Z","title_canon_sha256":"530690ecfd3319a7e120a0484fdaf563af34a9355a75900339e0517c8a33ff5a"},"schema_version":"1.0","source":{"id":"1706.00531","kind":"arxiv","version":1}},"canonical_sha256":"951955eb7c1b7ab5539d1f81e9f549ef66cc9c66b7390b06105217822d8eddea","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"951955eb7c1b7ab5539d1f81e9f549ef66cc9c66b7390b06105217822d8eddea","first_computed_at":"2026-05-18T00:43:12.762082Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:43:12.762082Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vFWPHyEhWblOvDR98+e4cXgcAzlJnvgA+0+7S2jMx4xXYgAxTWhx3Tj56Dz6lNfEq1fjBIl+fz9KDF09OA44BQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:43:12.762758Z","signed_message":"canonical_sha256_bytes"},"source_id":"1706.00531","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:84409a6e0c6899833ee8ddfbea9e52e0ec07c1305c1d416e65218b33185f3e9b","sha256:c043fa7aa0cdb8c4f698f0f5c9466a3470438f2dfe0ef141f526364178476622"],"state_sha256":"29313581fbc5d0e781c159ee0ccd30a47a97df620e86fd78e347ef2fe5df5faa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D1YuekownMAhXKmPI3KVr6T5Wq60ews51J5Y+MIaHoJjAzgsoYWI6it/mCKfGK3YLqu1muE5zjN9BKpt1/SKCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T23:48:38.209002Z","bundle_sha256":"2f851d7a60610089b6480488181e4914b90d6254ee45859c966035232ef96097"}}