{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:FEAG73M5XC5ZMMWOTIL7UG7UW4","short_pith_number":"pith:FEAG73M5","canonical_record":{"source":{"id":"1811.03692","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-08T22:08:12Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"1e039596215d0b189c380d6164faebe86e275f54709a62656a4265f02f77c4a6","abstract_canon_sha256":"7d930c9b0316b6e03ee7e084c045bd0fa813e305ff33479ed8d5a6d547947a6f"},"schema_version":"1.0"},"canonical_sha256":"29006fed9db8bb9632ce9a17fa1bf4b721e27962f78734f65e88485c603887bd","source":{"kind":"arxiv","id":"1811.03692","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.03692","created_at":"2026-05-17T23:50:36Z"},{"alias_kind":"arxiv_version","alias_value":"1811.03692v3","created_at":"2026-05-17T23:50:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.03692","created_at":"2026-05-17T23:50:36Z"},{"alias_kind":"pith_short_12","alias_value":"FEAG73M5XC5Z","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"FEAG73M5XC5ZMMWO","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"FEAG73M5","created_at":"2026-05-18T12:32:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:FEAG73M5XC5ZMMWOTIL7UG7UW4","target":"record","payload":{"canonical_record":{"source":{"id":"1811.03692","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-08T22:08:12Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"1e039596215d0b189c380d6164faebe86e275f54709a62656a4265f02f77c4a6","abstract_canon_sha256":"7d930c9b0316b6e03ee7e084c045bd0fa813e305ff33479ed8d5a6d547947a6f"},"schema_version":"1.0"},"canonical_sha256":"29006fed9db8bb9632ce9a17fa1bf4b721e27962f78734f65e88485c603887bd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:50:36.365715Z","signature_b64":"lDRdvevStqkTdFBQrhNGrOkjhdu3s+4JDj93M52xFHmjp1iIks2gW0sVK3HGvzFLlK1fCSFwbKrucL1tiYpJBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"29006fed9db8bb9632ce9a17fa1bf4b721e27962f78734f65e88485c603887bd","last_reissued_at":"2026-05-17T23:50:36.365196Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:50:36.365196Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.03692","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":"2026-05-17T23:50:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"deC2VK9ebqQoNGriMFnaWzgbuyjnK6ZK2BmASoCR8gDVFPliJtNNnJkbgmnRSO9CITX0rPZpoHLYWzvOrEeLBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T07:48:38.804484Z"},"content_sha256":"602735cd7e726d226b791116a7882e38b09dc2da1f865049a30f96a5e130a904","schema_version":"1.0","event_id":"sha256:602735cd7e726d226b791116a7882e38b09dc2da1f865049a30f96a5e130a904"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:FEAG73M5XC5ZMMWOTIL7UG7UW4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Mode matching in GANs through latent space learning and inversion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Aravind Jayendran, Deepak Mishra, Prathosh A. P., Santanu Chaudhury, Varun Srivastava","submitted_at":"2018-11-08T22:08:12Z","abstract_excerpt":"Generative adversarial networks (GANs) have shown remarkable success in generation of unstructured data, such as, natural images. However, discovery and separation of modes in the generated space, essential for several tasks beyond naive data generation, is still a challenge. In this paper, we address the problem of imposing desired modal properties on the generated space using a latent distribution, engineered in accordance with the modal properties of the true data distribution. This is achieved by training a latent space inversion network in tandem with the generative network using a diverg"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.03692","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":""},"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":"2026-05-17T23:50:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3K55jDC8AQbiOhnUiavexsnyhpf+NGEE4wnlieuvvH3Y44r1tRGfUKzKzAGhjnrJyZm/uXbNBTITJ1DgLA/RBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T07:48:38.804830Z"},"content_sha256":"19a5a937f90077ede46e52af7ce3520ff55d15bb1acf18c28ac00568dffdc46b","schema_version":"1.0","event_id":"sha256:19a5a937f90077ede46e52af7ce3520ff55d15bb1acf18c28ac00568dffdc46b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FEAG73M5XC5ZMMWOTIL7UG7UW4/bundle.json","state_url":"https://pith.science/pith/FEAG73M5XC5ZMMWOTIL7UG7UW4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FEAG73M5XC5ZMMWOTIL7UG7UW4/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":"2026-06-02T07:48:38Z","links":{"resolver":"https://pith.science/pith/FEAG73M5XC5ZMMWOTIL7UG7UW4","bundle":"https://pith.science/pith/FEAG73M5XC5ZMMWOTIL7UG7UW4/bundle.json","state":"https://pith.science/pith/FEAG73M5XC5ZMMWOTIL7UG7UW4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FEAG73M5XC5ZMMWOTIL7UG7UW4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:FEAG73M5XC5ZMMWOTIL7UG7UW4","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":"7d930c9b0316b6e03ee7e084c045bd0fa813e305ff33479ed8d5a6d547947a6f","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-08T22:08:12Z","title_canon_sha256":"1e039596215d0b189c380d6164faebe86e275f54709a62656a4265f02f77c4a6"},"schema_version":"1.0","source":{"id":"1811.03692","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.03692","created_at":"2026-05-17T23:50:36Z"},{"alias_kind":"arxiv_version","alias_value":"1811.03692v3","created_at":"2026-05-17T23:50:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.03692","created_at":"2026-05-17T23:50:36Z"},{"alias_kind":"pith_short_12","alias_value":"FEAG73M5XC5Z","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"FEAG73M5XC5ZMMWO","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"FEAG73M5","created_at":"2026-05-18T12:32:22Z"}],"graph_snapshots":[{"event_id":"sha256:19a5a937f90077ede46e52af7ce3520ff55d15bb1acf18c28ac00568dffdc46b","target":"graph","created_at":"2026-05-17T23:50:36Z","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":"Generative adversarial networks (GANs) have shown remarkable success in generation of unstructured data, such as, natural images. However, discovery and separation of modes in the generated space, essential for several tasks beyond naive data generation, is still a challenge. In this paper, we address the problem of imposing desired modal properties on the generated space using a latent distribution, engineered in accordance with the modal properties of the true data distribution. This is achieved by training a latent space inversion network in tandem with the generative network using a diverg","authors_text":"Aravind Jayendran, Deepak Mishra, Prathosh A. P., Santanu Chaudhury, Varun Srivastava","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-08T22:08:12Z","title":"Mode matching in GANs through latent space learning and inversion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.03692","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":"sha256:602735cd7e726d226b791116a7882e38b09dc2da1f865049a30f96a5e130a904","target":"record","created_at":"2026-05-17T23:50:36Z","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":"7d930c9b0316b6e03ee7e084c045bd0fa813e305ff33479ed8d5a6d547947a6f","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-08T22:08:12Z","title_canon_sha256":"1e039596215d0b189c380d6164faebe86e275f54709a62656a4265f02f77c4a6"},"schema_version":"1.0","source":{"id":"1811.03692","kind":"arxiv","version":3}},"canonical_sha256":"29006fed9db8bb9632ce9a17fa1bf4b721e27962f78734f65e88485c603887bd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"29006fed9db8bb9632ce9a17fa1bf4b721e27962f78734f65e88485c603887bd","first_computed_at":"2026-05-17T23:50:36.365196Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:50:36.365196Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lDRdvevStqkTdFBQrhNGrOkjhdu3s+4JDj93M52xFHmjp1iIks2gW0sVK3HGvzFLlK1fCSFwbKrucL1tiYpJBQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:50:36.365715Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.03692","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:602735cd7e726d226b791116a7882e38b09dc2da1f865049a30f96a5e130a904","sha256:19a5a937f90077ede46e52af7ce3520ff55d15bb1acf18c28ac00568dffdc46b"],"state_sha256":"dbe533f48ea1a0f0b124198c01e3cc9df6459a7c3ae21362ff1e235e2794b32e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qJqsq9q5CUmG+qpuO8T/yEx6+GBJVN6K9vNgjDSeBNh/v0XeHEl3sxiajX+VKCsBPxDukn8/U2M006FmSsHzBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T07:48:38.806983Z","bundle_sha256":"56cd7b5efb49fa1c9297c2fdc2b85049a27f16a43bc4afecd8ea4c257c990e46"}}