{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:2SXZBPQBTI4CB5NWLQX2T2M3LA","short_pith_number":"pith:2SXZBPQB","canonical_record":{"source":{"id":"1912.11615","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-25T08:04:52Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"f052109315549e51e520e708bc7973d1305e395b287cbc0e68e2279637514125","abstract_canon_sha256":"283924b7db3c20860e84d5bb490ef526e8b5a5a03cb00ce66de02a63114d3180"},"schema_version":"1.0"},"canonical_sha256":"d4af90be019a3820f5b65c2fa9e99b582ea5ec667c5f7ee46f7fe7fdde6f5a7d","source":{"kind":"arxiv","id":"1912.11615","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.11615","created_at":"2026-07-05T01:39:55Z"},{"alias_kind":"arxiv_version","alias_value":"1912.11615v2","created_at":"2026-07-05T01:39:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.11615","created_at":"2026-07-05T01:39:55Z"},{"alias_kind":"pith_short_12","alias_value":"2SXZBPQBTI4C","created_at":"2026-07-05T01:39:55Z"},{"alias_kind":"pith_short_16","alias_value":"2SXZBPQBTI4CB5NW","created_at":"2026-07-05T01:39:55Z"},{"alias_kind":"pith_short_8","alias_value":"2SXZBPQB","created_at":"2026-07-05T01:39:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:2SXZBPQBTI4CB5NWLQX2T2M3LA","target":"record","payload":{"canonical_record":{"source":{"id":"1912.11615","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-25T08:04:52Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"f052109315549e51e520e708bc7973d1305e395b287cbc0e68e2279637514125","abstract_canon_sha256":"283924b7db3c20860e84d5bb490ef526e8b5a5a03cb00ce66de02a63114d3180"},"schema_version":"1.0"},"canonical_sha256":"d4af90be019a3820f5b65c2fa9e99b582ea5ec667c5f7ee46f7fe7fdde6f5a7d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:39:55.577367Z","signature_b64":"PZkTGVOo9c/FRwlA4VKcug6qwtHYKd910NYvMKd0yGJjoCAN80d5WE/DrgCSKr/tFZJNZ/B9CRKkyjkUKZISBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d4af90be019a3820f5b65c2fa9e99b582ea5ec667c5f7ee46f7fe7fdde6f5a7d","last_reissued_at":"2026-07-05T01:39:55.576964Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:39:55.576964Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1912.11615","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:39:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qyiHBFHOxvBdMCjXFS1bUOdD6psdAjvvOH09mg32shbgyI5HrYWSkZx/uEra0qdPoOor+dsznG6wUJCOLd+ZCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T08:19:50.193249Z"},"content_sha256":"fb4149c4d1af71696f1e960c68703bb769d4af1ecf9c2b6b4b36dadee592e924","schema_version":"1.0","event_id":"sha256:fb4149c4d1af71696f1e960c68703bb769d4af1ecf9c2b6b4b36dadee592e924"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:2SXZBPQBTI4CB5NWLQX2T2M3LA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Graph Similarity Learning: A Survey","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Guixiang Ma, Nesreen K. Ahmed, Philip S. Yu, Theodore L. Willke","submitted_at":"2019-12-25T08:04:52Z","abstract_excerpt":"In many domains where data are represented as graphs, learning a similarity metric among graphs is considered a key problem, which can further facilitate various learning tasks, such as classification, clustering, and similarity search. Recently, there has been an increasing interest in deep graph similarity learning, where the key idea is to learn a deep learning model that maps input graphs to a target space such that the distance in the target space approximates the structural distance in the input space. Here, we provide a comprehensive review of the existing literature of deep graph simil"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.11615","kind":"arxiv","version":2},"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/1912.11615/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":"2026-07-05T01:39:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WEZ8R6YLlo3rm68H28md5JbaiejU+OoGyR/KBDkqwnM3UgdKB2SlzETEu7KFJ71BHXetELq+uAp6Jlax9oqdBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T08:19:50.193650Z"},"content_sha256":"5ecf84841608e467ea6ea4794f9a5b37b3d334e292cc69b00a1685b7797341bd","schema_version":"1.0","event_id":"sha256:5ecf84841608e467ea6ea4794f9a5b37b3d334e292cc69b00a1685b7797341bd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2SXZBPQBTI4CB5NWLQX2T2M3LA/bundle.json","state_url":"https://pith.science/pith/2SXZBPQBTI4CB5NWLQX2T2M3LA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2SXZBPQBTI4CB5NWLQX2T2M3LA/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":"2026-07-07T08:19:50Z","links":{"resolver":"https://pith.science/pith/2SXZBPQBTI4CB5NWLQX2T2M3LA","bundle":"https://pith.science/pith/2SXZBPQBTI4CB5NWLQX2T2M3LA/bundle.json","state":"https://pith.science/pith/2SXZBPQBTI4CB5NWLQX2T2M3LA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2SXZBPQBTI4CB5NWLQX2T2M3LA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:2SXZBPQBTI4CB5NWLQX2T2M3LA","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":"283924b7db3c20860e84d5bb490ef526e8b5a5a03cb00ce66de02a63114d3180","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-25T08:04:52Z","title_canon_sha256":"f052109315549e51e520e708bc7973d1305e395b287cbc0e68e2279637514125"},"schema_version":"1.0","source":{"id":"1912.11615","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.11615","created_at":"2026-07-05T01:39:55Z"},{"alias_kind":"arxiv_version","alias_value":"1912.11615v2","created_at":"2026-07-05T01:39:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.11615","created_at":"2026-07-05T01:39:55Z"},{"alias_kind":"pith_short_12","alias_value":"2SXZBPQBTI4C","created_at":"2026-07-05T01:39:55Z"},{"alias_kind":"pith_short_16","alias_value":"2SXZBPQBTI4CB5NW","created_at":"2026-07-05T01:39:55Z"},{"alias_kind":"pith_short_8","alias_value":"2SXZBPQB","created_at":"2026-07-05T01:39:55Z"}],"graph_snapshots":[{"event_id":"sha256:5ecf84841608e467ea6ea4794f9a5b37b3d334e292cc69b00a1685b7797341bd","target":"graph","created_at":"2026-07-05T01:39:55Z","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/1912.11615/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In many domains where data are represented as graphs, learning a similarity metric among graphs is considered a key problem, which can further facilitate various learning tasks, such as classification, clustering, and similarity search. Recently, there has been an increasing interest in deep graph similarity learning, where the key idea is to learn a deep learning model that maps input graphs to a target space such that the distance in the target space approximates the structural distance in the input space. Here, we provide a comprehensive review of the existing literature of deep graph simil","authors_text":"Guixiang Ma, Nesreen K. Ahmed, Philip S. Yu, Theodore L. Willke","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-25T08:04:52Z","title":"Deep Graph Similarity Learning: A Survey"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.11615","kind":"arxiv","version":2},"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:fb4149c4d1af71696f1e960c68703bb769d4af1ecf9c2b6b4b36dadee592e924","target":"record","created_at":"2026-07-05T01:39:55Z","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":"283924b7db3c20860e84d5bb490ef526e8b5a5a03cb00ce66de02a63114d3180","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-25T08:04:52Z","title_canon_sha256":"f052109315549e51e520e708bc7973d1305e395b287cbc0e68e2279637514125"},"schema_version":"1.0","source":{"id":"1912.11615","kind":"arxiv","version":2}},"canonical_sha256":"d4af90be019a3820f5b65c2fa9e99b582ea5ec667c5f7ee46f7fe7fdde6f5a7d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d4af90be019a3820f5b65c2fa9e99b582ea5ec667c5f7ee46f7fe7fdde6f5a7d","first_computed_at":"2026-07-05T01:39:55.576964Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:39:55.576964Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PZkTGVOo9c/FRwlA4VKcug6qwtHYKd910NYvMKd0yGJjoCAN80d5WE/DrgCSKr/tFZJNZ/B9CRKkyjkUKZISBw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:39:55.577367Z","signed_message":"canonical_sha256_bytes"},"source_id":"1912.11615","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fb4149c4d1af71696f1e960c68703bb769d4af1ecf9c2b6b4b36dadee592e924","sha256:5ecf84841608e467ea6ea4794f9a5b37b3d334e292cc69b00a1685b7797341bd"],"state_sha256":"2ef53b8cb8536893e8a64d2b018756c0fff576d3c0dd8c819c8b9849a8efe494"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"klb6j3UrGtcaqDHId6YTnDkAiLCIO0zzbev302OR60PCsi3wPWPr4laWVfzcUvTdbIFsiZ41rGerSiF2X0gRAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T08:19:50.196754Z","bundle_sha256":"44b5dcd79d9fc1bf567df4da11d97c000fcdd7b86cb5f7ee17f3a328e48a0f34"}}