{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:UIEP27YUQJLMURPTYDPDCPTB5H","short_pith_number":"pith:UIEP27YU","canonical_record":{"source":{"id":"1806.03182","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-06-07T01:55:06Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"40288f1674e0caad6b88379315ada5050d1dadd689bd91e1ce9d56b5fc4c6a23","abstract_canon_sha256":"4dfe11f353e037f52b072c872e67357a4d00fc47b83f6ccb3a3f159672da678a"},"schema_version":"1.0"},"canonical_sha256":"a208fd7f148256ca45f3c0de313e61e9c53b79c3de14a7d77692eafcf79e3998","source":{"kind":"arxiv","id":"1806.03182","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.03182","created_at":"2026-05-18T00:13:49Z"},{"alias_kind":"arxiv_version","alias_value":"1806.03182v1","created_at":"2026-05-18T00:13:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.03182","created_at":"2026-05-18T00:13:49Z"},{"alias_kind":"pith_short_12","alias_value":"UIEP27YUQJLM","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"UIEP27YUQJLMURPT","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"UIEP27YU","created_at":"2026-05-18T12:32:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:UIEP27YUQJLMURPTYDPDCPTB5H","target":"record","payload":{"canonical_record":{"source":{"id":"1806.03182","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-06-07T01:55:06Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"40288f1674e0caad6b88379315ada5050d1dadd689bd91e1ce9d56b5fc4c6a23","abstract_canon_sha256":"4dfe11f353e037f52b072c872e67357a4d00fc47b83f6ccb3a3f159672da678a"},"schema_version":"1.0"},"canonical_sha256":"a208fd7f148256ca45f3c0de313e61e9c53b79c3de14a7d77692eafcf79e3998","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:13:49.362745Z","signature_b64":"c4Ts7igOEeq/2Apbrdb7mEhW47S1LgDxbI0Zh5sVeSYdrMC+RRPe6FgB9QEvE/6JKL8T46mAqj5Q0T+Wvl49Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a208fd7f148256ca45f3c0de313e61e9c53b79c3de14a7d77692eafcf79e3998","last_reissued_at":"2026-05-18T00:13:49.362070Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:13:49.362070Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.03182","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":"2026-05-18T00:13:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CHRG6Zm+GAAESs6BEMj0VfDEfnjG0zX/pt392jHGa8UQf65s9i+2XPB6bkdBkrIXBNV3FTVQ7QJ8/F6PXvjYCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-19T23:59:00.394478Z"},"content_sha256":"afab8ea99c452df0e3c7c5fe94be6f2b746edcf0d01e5c60d360e6d9673d9814","schema_version":"1.0","event_id":"sha256:afab8ea99c452df0e3c7c5fe94be6f2b746edcf0d01e5c60d360e6d9673d9814"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:UIEP27YUQJLMURPTYDPDCPTB5H","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep learning based inverse method for layout design","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"eess.SP","authors_text":"Wenjing Ye, Yujie Zhang","submitted_at":"2018-06-07T01:55:06Z","abstract_excerpt":"Layout design with complex constraints is a challenging problem to solve due to the non-uniqueness of the solution and the difficulties in incorporating the constraints into the conventional optimization-based methods. In this paper, we propose a design method based on the recently developed machine learning technique, Variational Autoencoder (VAE). We utilize the learning capability of the VAE to learn the constraints and the generative capability of the VAE to generate design candidates that automatically satisfy all the constraints. As such, no constraints need to be imposed during the desi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.03182","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":"2026-05-18T00:13:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DBl/eI0jRS3RdGYB0sFzsurZd/MfgDsOU2FAvpdZwbtB84RT5nPJQ3kvIaJjH3flNm4gtCQL2TPxUzAXyt0UCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-19T23:59:00.395161Z"},"content_sha256":"9f0cac85f4bc48f501a4ad5f40d401ff17c8ce3227cacb1e24064cdd16e7d01c","schema_version":"1.0","event_id":"sha256:9f0cac85f4bc48f501a4ad5f40d401ff17c8ce3227cacb1e24064cdd16e7d01c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UIEP27YUQJLMURPTYDPDCPTB5H/bundle.json","state_url":"https://pith.science/pith/UIEP27YUQJLMURPTYDPDCPTB5H/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UIEP27YUQJLMURPTYDPDCPTB5H/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":"2026-05-19T23:59:00Z","links":{"resolver":"https://pith.science/pith/UIEP27YUQJLMURPTYDPDCPTB5H","bundle":"https://pith.science/pith/UIEP27YUQJLMURPTYDPDCPTB5H/bundle.json","state":"https://pith.science/pith/UIEP27YUQJLMURPTYDPDCPTB5H/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UIEP27YUQJLMURPTYDPDCPTB5H/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:UIEP27YUQJLMURPTYDPDCPTB5H","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":"4dfe11f353e037f52b072c872e67357a4d00fc47b83f6ccb3a3f159672da678a","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-06-07T01:55:06Z","title_canon_sha256":"40288f1674e0caad6b88379315ada5050d1dadd689bd91e1ce9d56b5fc4c6a23"},"schema_version":"1.0","source":{"id":"1806.03182","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.03182","created_at":"2026-05-18T00:13:49Z"},{"alias_kind":"arxiv_version","alias_value":"1806.03182v1","created_at":"2026-05-18T00:13:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.03182","created_at":"2026-05-18T00:13:49Z"},{"alias_kind":"pith_short_12","alias_value":"UIEP27YUQJLM","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"UIEP27YUQJLMURPT","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"UIEP27YU","created_at":"2026-05-18T12:32:56Z"}],"graph_snapshots":[{"event_id":"sha256:9f0cac85f4bc48f501a4ad5f40d401ff17c8ce3227cacb1e24064cdd16e7d01c","target":"graph","created_at":"2026-05-18T00:13:49Z","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":"Layout design with complex constraints is a challenging problem to solve due to the non-uniqueness of the solution and the difficulties in incorporating the constraints into the conventional optimization-based methods. In this paper, we propose a design method based on the recently developed machine learning technique, Variational Autoencoder (VAE). We utilize the learning capability of the VAE to learn the constraints and the generative capability of the VAE to generate design candidates that automatically satisfy all the constraints. As such, no constraints need to be imposed during the desi","authors_text":"Wenjing Ye, Yujie Zhang","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-06-07T01:55:06Z","title":"Deep learning based inverse method for layout design"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.03182","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:afab8ea99c452df0e3c7c5fe94be6f2b746edcf0d01e5c60d360e6d9673d9814","target":"record","created_at":"2026-05-18T00:13:49Z","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":"4dfe11f353e037f52b072c872e67357a4d00fc47b83f6ccb3a3f159672da678a","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-06-07T01:55:06Z","title_canon_sha256":"40288f1674e0caad6b88379315ada5050d1dadd689bd91e1ce9d56b5fc4c6a23"},"schema_version":"1.0","source":{"id":"1806.03182","kind":"arxiv","version":1}},"canonical_sha256":"a208fd7f148256ca45f3c0de313e61e9c53b79c3de14a7d77692eafcf79e3998","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a208fd7f148256ca45f3c0de313e61e9c53b79c3de14a7d77692eafcf79e3998","first_computed_at":"2026-05-18T00:13:49.362070Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:13:49.362070Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"c4Ts7igOEeq/2Apbrdb7mEhW47S1LgDxbI0Zh5sVeSYdrMC+RRPe6FgB9QEvE/6JKL8T46mAqj5Q0T+Wvl49Cg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:13:49.362745Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.03182","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:afab8ea99c452df0e3c7c5fe94be6f2b746edcf0d01e5c60d360e6d9673d9814","sha256:9f0cac85f4bc48f501a4ad5f40d401ff17c8ce3227cacb1e24064cdd16e7d01c"],"state_sha256":"809d68dd49a0f345daeb575084adb97d0ecad53a07f065524cbb983fcfc89451"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I+ZI7v9/+nY8pSIt2SMirXLnx+l11OgKGrqvDxvW67x25MAXS9VaiP2ik9vCGJnVfDA/OTu5uCKCsm4jmx56Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-19T23:59:00.398886Z","bundle_sha256":"b84a73459d31fbaedce1ad26a07a1859fd41a0aad57f4eb039e9a057cbeb9a3b"}}