{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:VEE6VL4N4JZGUMUFNKRLVTUJW5","short_pith_number":"pith:VEE6VL4N","canonical_record":{"source":{"id":"2203.16437","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2022-03-30T16:35:26Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"8ee4315e9b8d1b2bf803584ce893456e624ad0eccd50ce2435c38a697c9abab9","abstract_canon_sha256":"69807b3817ac6ad766077a4cf1adc5ce3c31a8cbeb2165b3eaead9d04ebff5d8"},"schema_version":"1.0"},"canonical_sha256":"a909eaaf8de2726a32856aa2bace89b76b6a706e984f96bcb54cdff8e1b50bc4","source":{"kind":"arxiv","id":"2203.16437","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.16437","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"arxiv_version","alias_value":"2203.16437v3","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.16437","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"pith_short_12","alias_value":"VEE6VL4N4JZG","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"pith_short_16","alias_value":"VEE6VL4N4JZGUMUF","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"pith_short_8","alias_value":"VEE6VL4N","created_at":"2026-07-05T05:05:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:VEE6VL4N4JZGUMUFNKRLVTUJW5","target":"record","payload":{"canonical_record":{"source":{"id":"2203.16437","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2022-03-30T16:35:26Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"8ee4315e9b8d1b2bf803584ce893456e624ad0eccd50ce2435c38a697c9abab9","abstract_canon_sha256":"69807b3817ac6ad766077a4cf1adc5ce3c31a8cbeb2165b3eaead9d04ebff5d8"},"schema_version":"1.0"},"canonical_sha256":"a909eaaf8de2726a32856aa2bace89b76b6a706e984f96bcb54cdff8e1b50bc4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:05:03.935600Z","signature_b64":"yWrEGLvtDZ8GjULRRgYYmru+eue9yJDgpUzLt0YUQTHLWJY7bzCWlv7aoxvqDrqZdfAKArPfgOpLPz+l/vk5CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a909eaaf8de2726a32856aa2bace89b76b6a706e984f96bcb54cdff8e1b50bc4","last_reissued_at":"2026-07-05T05:05:03.935167Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:05:03.935167Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.16437","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:05:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E/T4vxudTXGUphBVlQNrzbbEahThCboaqOCOWUIPiO6eFGvNqEGodzghFCkDjwJfbD4utt+gSsIuodBSmi5tAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T12:06:43.718837Z"},"content_sha256":"dbd126319ca24b02f76ef770fbed3d6a81f0b3ba6a3204398fd858b41b8cff43","schema_version":"1.0","event_id":"sha256:dbd126319ca24b02f76ef770fbed3d6a81f0b3ba6a3204398fd858b41b8cff43"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:VEE6VL4N4JZGUMUFNKRLVTUJW5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Weakly supervised causal representation learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Johann Brehmer, Phillip Lippe, Pim de Haan, Taco Cohen","submitted_at":"2022-03-30T16:35:26Z","abstract_excerpt":"Learning high-level causal representations together with a causal model from unstructured low-level data such as pixels is impossible from observational data alone. We prove under mild assumptions that this representation is however identifiable in a weakly supervised setting. This involves a dataset with paired samples before and after random, unknown interventions, but no further labels. We then introduce implicit latent causal models, variational autoencoders that represent causal variables and causal structure without having to optimize an explicit discrete graph structure. On simple image"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.16437","kind":"arxiv","version":3},"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/2203.16437/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":"2026-07-05T05:05:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cfdxLwjSJCNCN0wHeGJ8THttgM/x1R4UuxqIqpx/+r7pjYrb7IVbj2ss+FEH2CtOOZwoqeAlGYpN2341t2j6Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T12:06:43.719336Z"},"content_sha256":"fa440acd7219d4a97e21ccc601a894e6f7ed5542f11b123ab3234f97241c4595","schema_version":"1.0","event_id":"sha256:fa440acd7219d4a97e21ccc601a894e6f7ed5542f11b123ab3234f97241c4595"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VEE6VL4N4JZGUMUFNKRLVTUJW5/bundle.json","state_url":"https://pith.science/pith/VEE6VL4N4JZGUMUFNKRLVTUJW5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VEE6VL4N4JZGUMUFNKRLVTUJW5/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":"2026-08-14T12:06:43Z","links":{"resolver":"https://pith.science/pith/VEE6VL4N4JZGUMUFNKRLVTUJW5","bundle":"https://pith.science/pith/VEE6VL4N4JZGUMUFNKRLVTUJW5/bundle.json","state":"https://pith.science/pith/VEE6VL4N4JZGUMUFNKRLVTUJW5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VEE6VL4N4JZGUMUFNKRLVTUJW5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:VEE6VL4N4JZGUMUFNKRLVTUJW5","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":"69807b3817ac6ad766077a4cf1adc5ce3c31a8cbeb2165b3eaead9d04ebff5d8","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2022-03-30T16:35:26Z","title_canon_sha256":"8ee4315e9b8d1b2bf803584ce893456e624ad0eccd50ce2435c38a697c9abab9"},"schema_version":"1.0","source":{"id":"2203.16437","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.16437","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"arxiv_version","alias_value":"2203.16437v3","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.16437","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"pith_short_12","alias_value":"VEE6VL4N4JZG","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"pith_short_16","alias_value":"VEE6VL4N4JZGUMUF","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"pith_short_8","alias_value":"VEE6VL4N","created_at":"2026-07-05T05:05:03Z"}],"graph_snapshots":[{"event_id":"sha256:fa440acd7219d4a97e21ccc601a894e6f7ed5542f11b123ab3234f97241c4595","target":"graph","created_at":"2026-07-05T05:05:03Z","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/2203.16437/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning high-level causal representations together with a causal model from unstructured low-level data such as pixels is impossible from observational data alone. We prove under mild assumptions that this representation is however identifiable in a weakly supervised setting. This involves a dataset with paired samples before and after random, unknown interventions, but no further labels. We then introduce implicit latent causal models, variational autoencoders that represent causal variables and causal structure without having to optimize an explicit discrete graph structure. On simple image","authors_text":"Johann Brehmer, Phillip Lippe, Pim de Haan, Taco Cohen","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2022-03-30T16:35:26Z","title":"Weakly supervised causal representation learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.16437","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:dbd126319ca24b02f76ef770fbed3d6a81f0b3ba6a3204398fd858b41b8cff43","target":"record","created_at":"2026-07-05T05:05:03Z","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":"69807b3817ac6ad766077a4cf1adc5ce3c31a8cbeb2165b3eaead9d04ebff5d8","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2022-03-30T16:35:26Z","title_canon_sha256":"8ee4315e9b8d1b2bf803584ce893456e624ad0eccd50ce2435c38a697c9abab9"},"schema_version":"1.0","source":{"id":"2203.16437","kind":"arxiv","version":3}},"canonical_sha256":"a909eaaf8de2726a32856aa2bace89b76b6a706e984f96bcb54cdff8e1b50bc4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a909eaaf8de2726a32856aa2bace89b76b6a706e984f96bcb54cdff8e1b50bc4","first_computed_at":"2026-07-05T05:05:03.935167Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:05:03.935167Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yWrEGLvtDZ8GjULRRgYYmru+eue9yJDgpUzLt0YUQTHLWJY7bzCWlv7aoxvqDrqZdfAKArPfgOpLPz+l/vk5CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:05:03.935600Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.16437","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dbd126319ca24b02f76ef770fbed3d6a81f0b3ba6a3204398fd858b41b8cff43","sha256:fa440acd7219d4a97e21ccc601a894e6f7ed5542f11b123ab3234f97241c4595"],"state_sha256":"43c1b19de8b1a7b6314bc34ac9c98b3ac60cf5f7f0b3d8aab7060b5c8ec1cc5a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7lwXVSfN3jQdC3AUOOyNyrmnQBX6XpIiouB1fMkGXM/KUjia8TA5V/5pl70zQpQ92MbEwvxBCeMMAlm8O6UOBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T12:06:43.723582Z","bundle_sha256":"b5ccf58a9cfb7bb2ace96c3c53611e2ff5fca8482d1a96f668eb819175c9b4fa"}}