{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:HPUBJG3NL3U7PTTSZX7RISBGKJ","short_pith_number":"pith:HPUBJG3N","canonical_record":{"source":{"id":"1712.00634","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T16:44:10Z","cross_cats_sorted":["cs.AI","cs.RO","cs.SY","math.OC"],"title_canon_sha256":"2158ece1e9b2fdce5724172bb8a84941bd758f11bb9c57f80d2a79d0f72b5aa1","abstract_canon_sha256":"ab1da1a06ca344292789e40d628fc79448399d577235b90f2489ea0093d122b5"},"schema_version":"1.0"},"canonical_sha256":"3be8149b6d5ee9f7ce72cdff144826527e0fe565af23c41339b73cc3b923ca07","source":{"kind":"arxiv","id":"1712.00634","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.00634","created_at":"2026-05-18T00:29:04Z"},{"alias_kind":"arxiv_version","alias_value":"1712.00634v1","created_at":"2026-05-18T00:29:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.00634","created_at":"2026-05-18T00:29:04Z"},{"alias_kind":"pith_short_12","alias_value":"HPUBJG3NL3U7","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"HPUBJG3NL3U7PTTS","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"HPUBJG3N","created_at":"2026-05-18T12:31:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:HPUBJG3NL3U7PTTSZX7RISBGKJ","target":"record","payload":{"canonical_record":{"source":{"id":"1712.00634","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T16:44:10Z","cross_cats_sorted":["cs.AI","cs.RO","cs.SY","math.OC"],"title_canon_sha256":"2158ece1e9b2fdce5724172bb8a84941bd758f11bb9c57f80d2a79d0f72b5aa1","abstract_canon_sha256":"ab1da1a06ca344292789e40d628fc79448399d577235b90f2489ea0093d122b5"},"schema_version":"1.0"},"canonical_sha256":"3be8149b6d5ee9f7ce72cdff144826527e0fe565af23c41339b73cc3b923ca07","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:29:04.531838Z","signature_b64":"YSSGwrTJBlrazWLHwJrtjOhfwVeLr3agxGmZSsKZ8bw6xFXvgHpf6ujAPNM1mE/6PcGxu8pPUVb5LesQbbqxBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3be8149b6d5ee9f7ce72cdff144826527e0fe565af23c41339b73cc3b923ca07","last_reissued_at":"2026-05-18T00:29:04.531076Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:29:04.531076Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1712.00634","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":"2026-05-18T00:29:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LdtAAgIWhmVGHnBL3GoKZv1iMlzkFpruAmdU2LKKOzHqYCYH2l/x9LaPoqonShnWWaTR7bzSNdyl4QZSPGDlDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T11:02:37.949023Z"},"content_sha256":"2c5912ec2f923dacf2899453103569d2ff90ef76c84e13853b4c889701050dd7","schema_version":"1.0","event_id":"sha256:2c5912ec2f923dacf2899453103569d2ff90ef76c84e13853b4c889701050dd7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:HPUBJG3NL3U7PTTSZX7RISBGKJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PFAx: Predictable Feature Analysis to Perform Control","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.RO","cs.SY","math.OC"],"primary_cat":"cs.LG","authors_text":"Laurenz Wiskott, Stefan Richthofer","submitted_at":"2017-12-02T16:44:10Z","abstract_excerpt":"Predictable Feature Analysis (PFA) (Richthofer, Wiskott, ICMLA 2015) is an algorithm that performs dimensionality reduction on high dimensional input signal. It extracts those subsignals that are most predictable according to a certain prediction model. We refer to these extracted signals as predictable features.\n  In this work we extend the notion of PFA to take supplementary information into account for improving its predictions. Such information can be a multidimensional signal like the main input to PFA, but is regarded external. That means it won't participate in the feature extraction - "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.00634","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":"2026-05-18T00:29:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b47zJrFUoEYVIjCdVl0/Z8rHQnWHOsPReiU0VdRh5DYQ0e8BEqsxCN8MSICB/Ja9+7cBnIBVHHhH0p7yQ4ApDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T11:02:37.949386Z"},"content_sha256":"4533b9efa23bd4856fdc7d288e020dfe0d41b48ef7d40f8a38c6db51558196ba","schema_version":"1.0","event_id":"sha256:4533b9efa23bd4856fdc7d288e020dfe0d41b48ef7d40f8a38c6db51558196ba"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HPUBJG3NL3U7PTTSZX7RISBGKJ/bundle.json","state_url":"https://pith.science/pith/HPUBJG3NL3U7PTTSZX7RISBGKJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HPUBJG3NL3U7PTTSZX7RISBGKJ/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":"2026-06-11T11:02:37Z","links":{"resolver":"https://pith.science/pith/HPUBJG3NL3U7PTTSZX7RISBGKJ","bundle":"https://pith.science/pith/HPUBJG3NL3U7PTTSZX7RISBGKJ/bundle.json","state":"https://pith.science/pith/HPUBJG3NL3U7PTTSZX7RISBGKJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HPUBJG3NL3U7PTTSZX7RISBGKJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:HPUBJG3NL3U7PTTSZX7RISBGKJ","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":"ab1da1a06ca344292789e40d628fc79448399d577235b90f2489ea0093d122b5","cross_cats_sorted":["cs.AI","cs.RO","cs.SY","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T16:44:10Z","title_canon_sha256":"2158ece1e9b2fdce5724172bb8a84941bd758f11bb9c57f80d2a79d0f72b5aa1"},"schema_version":"1.0","source":{"id":"1712.00634","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.00634","created_at":"2026-05-18T00:29:04Z"},{"alias_kind":"arxiv_version","alias_value":"1712.00634v1","created_at":"2026-05-18T00:29:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.00634","created_at":"2026-05-18T00:29:04Z"},{"alias_kind":"pith_short_12","alias_value":"HPUBJG3NL3U7","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"HPUBJG3NL3U7PTTS","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"HPUBJG3N","created_at":"2026-05-18T12:31:18Z"}],"graph_snapshots":[{"event_id":"sha256:4533b9efa23bd4856fdc7d288e020dfe0d41b48ef7d40f8a38c6db51558196ba","target":"graph","created_at":"2026-05-18T00:29:04Z","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":"Predictable Feature Analysis (PFA) (Richthofer, Wiskott, ICMLA 2015) is an algorithm that performs dimensionality reduction on high dimensional input signal. It extracts those subsignals that are most predictable according to a certain prediction model. We refer to these extracted signals as predictable features.\n  In this work we extend the notion of PFA to take supplementary information into account for improving its predictions. Such information can be a multidimensional signal like the main input to PFA, but is regarded external. That means it won't participate in the feature extraction - ","authors_text":"Laurenz Wiskott, Stefan Richthofer","cross_cats":["cs.AI","cs.RO","cs.SY","math.OC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T16:44:10Z","title":"PFAx: Predictable Feature Analysis to Perform Control"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.00634","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":"sha256:2c5912ec2f923dacf2899453103569d2ff90ef76c84e13853b4c889701050dd7","target":"record","created_at":"2026-05-18T00:29:04Z","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":"ab1da1a06ca344292789e40d628fc79448399d577235b90f2489ea0093d122b5","cross_cats_sorted":["cs.AI","cs.RO","cs.SY","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T16:44:10Z","title_canon_sha256":"2158ece1e9b2fdce5724172bb8a84941bd758f11bb9c57f80d2a79d0f72b5aa1"},"schema_version":"1.0","source":{"id":"1712.00634","kind":"arxiv","version":1}},"canonical_sha256":"3be8149b6d5ee9f7ce72cdff144826527e0fe565af23c41339b73cc3b923ca07","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3be8149b6d5ee9f7ce72cdff144826527e0fe565af23c41339b73cc3b923ca07","first_computed_at":"2026-05-18T00:29:04.531076Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:29:04.531076Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YSSGwrTJBlrazWLHwJrtjOhfwVeLr3agxGmZSsKZ8bw6xFXvgHpf6ujAPNM1mE/6PcGxu8pPUVb5LesQbbqxBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:29:04.531838Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.00634","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2c5912ec2f923dacf2899453103569d2ff90ef76c84e13853b4c889701050dd7","sha256:4533b9efa23bd4856fdc7d288e020dfe0d41b48ef7d40f8a38c6db51558196ba"],"state_sha256":"f789bf875df99c1fd3c876c9aaaa2b9b6522269ba49a5d791718c1e38d4b4ae5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0N54tIZd/e+2D6E0c+xR5aGPZdbex6ZJqxXJlPMpFX0I26i+2PBn3xLG8XKK/3lLbmcZdmnh8OTx5KGmEcbWDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T11:02:37.951379Z","bundle_sha256":"7a7eef2038e94a2b0bf6510657e6b0216cbaf61462db7f2cbb7dfcb8f6fa0525"}}