{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:RXXB7PRABEX3P5IN7QKV4TDJXI","short_pith_number":"pith:RXXB7PRA","canonical_record":{"source":{"id":"1904.06316","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-12T16:47:30Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"ce46d2bd73cfa8a262c9cb87b6d686170c9d8343bd10f95d0ab2d20ec1f370c1","abstract_canon_sha256":"fe242f4629f1cc57a088c08ddaec0cd39b8dfe272236990116705cbff6fb6d04"},"schema_version":"1.0"},"canonical_sha256":"8dee1fbe20092fb7f50dfc155e4c69ba042c0e94b8923ed9d0ff94034cbb6ec0","source":{"kind":"arxiv","id":"1904.06316","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.06316","created_at":"2026-05-17T23:48:43Z"},{"alias_kind":"arxiv_version","alias_value":"1904.06316v1","created_at":"2026-05-17T23:48:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.06316","created_at":"2026-05-17T23:48:43Z"},{"alias_kind":"pith_short_12","alias_value":"RXXB7PRABEX3","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"RXXB7PRABEX3P5IN","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"RXXB7PRA","created_at":"2026-05-18T12:33:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:RXXB7PRABEX3P5IN7QKV4TDJXI","target":"record","payload":{"canonical_record":{"source":{"id":"1904.06316","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-12T16:47:30Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"ce46d2bd73cfa8a262c9cb87b6d686170c9d8343bd10f95d0ab2d20ec1f370c1","abstract_canon_sha256":"fe242f4629f1cc57a088c08ddaec0cd39b8dfe272236990116705cbff6fb6d04"},"schema_version":"1.0"},"canonical_sha256":"8dee1fbe20092fb7f50dfc155e4c69ba042c0e94b8923ed9d0ff94034cbb6ec0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:43.604046Z","signature_b64":"2MNTtQl0xHR7kehd2FpPWMYYWsNEisZfw3OOXruoursPI3OE05IhctJ94Sp7Qp2bj1lB8sgVMC4GiHO+MpMaCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8dee1fbe20092fb7f50dfc155e4c69ba042c0e94b8923ed9d0ff94034cbb6ec0","last_reissued_at":"2026-05-17T23:48:43.603558Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:43.603558Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.06316","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":"2026-05-17T23:48:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uxAXmULh4e89qQKqGHx0A26wZCIsg8erB7I4wuJwdR/hUOVo9ELvTnzombE1/UaYXJ5W9zCatWBG2qvDrf0hAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T19:25:11.654122Z"},"content_sha256":"99f294c74df855cc2b136a3c61123a16812ac5b329eec6083a5055c2228bdd00","schema_version":"1.0","event_id":"sha256:99f294c74df855cc2b136a3c61123a16812ac5b329eec6083a5055c2228bdd00"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:RXXB7PRABEX3P5IN7QKV4TDJXI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Spatio-Temporal Deep Graph Infomax","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Aaron Solomon, C\\u{a}t\\u{a}lina Cangea, Felix L. Opolka, Petar Veli\\v{c}kovi\\'c, Pietro Li\\`o, R Devon Hjelm","submitted_at":"2019-04-12T16:47:30Z","abstract_excerpt":"Spatio-temporal graphs such as traffic networks or gene regulatory systems present challenges for the existing deep learning methods due to the complexity of structural changes over time. To address these issues, we introduce Spatio-Temporal Deep Graph Infomax (STDGI)---a fully unsupervised node representation learning approach based on mutual information maximization that exploits both the temporal and spatial dynamics of the graph. Our model tackles the challenging task of node-level regression by training embeddings to maximize the mutual information between patches of the graph, at any giv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.06316","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":"2026-05-17T23:48:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SoEhHL4MhldSHZpqMyXXWCcFLZf4s79x2NboEEn0aHeLDFjmH98WU9pB9Z4aUE3R/AmVVwZLrJyHRdOo6NPWAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T19:25:11.654475Z"},"content_sha256":"b5623d538165fff855e22ec7c9c3b09efafd9020974e039f34e5df286b563fb4","schema_version":"1.0","event_id":"sha256:b5623d538165fff855e22ec7c9c3b09efafd9020974e039f34e5df286b563fb4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RXXB7PRABEX3P5IN7QKV4TDJXI/bundle.json","state_url":"https://pith.science/pith/RXXB7PRABEX3P5IN7QKV4TDJXI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RXXB7PRABEX3P5IN7QKV4TDJXI/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":"2026-06-03T19:25:11Z","links":{"resolver":"https://pith.science/pith/RXXB7PRABEX3P5IN7QKV4TDJXI","bundle":"https://pith.science/pith/RXXB7PRABEX3P5IN7QKV4TDJXI/bundle.json","state":"https://pith.science/pith/RXXB7PRABEX3P5IN7QKV4TDJXI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RXXB7PRABEX3P5IN7QKV4TDJXI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:RXXB7PRABEX3P5IN7QKV4TDJXI","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":"fe242f4629f1cc57a088c08ddaec0cd39b8dfe272236990116705cbff6fb6d04","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-12T16:47:30Z","title_canon_sha256":"ce46d2bd73cfa8a262c9cb87b6d686170c9d8343bd10f95d0ab2d20ec1f370c1"},"schema_version":"1.0","source":{"id":"1904.06316","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.06316","created_at":"2026-05-17T23:48:43Z"},{"alias_kind":"arxiv_version","alias_value":"1904.06316v1","created_at":"2026-05-17T23:48:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.06316","created_at":"2026-05-17T23:48:43Z"},{"alias_kind":"pith_short_12","alias_value":"RXXB7PRABEX3","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"RXXB7PRABEX3P5IN","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"RXXB7PRA","created_at":"2026-05-18T12:33:27Z"}],"graph_snapshots":[{"event_id":"sha256:b5623d538165fff855e22ec7c9c3b09efafd9020974e039f34e5df286b563fb4","target":"graph","created_at":"2026-05-17T23:48:43Z","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":"Spatio-temporal graphs such as traffic networks or gene regulatory systems present challenges for the existing deep learning methods due to the complexity of structural changes over time. To address these issues, we introduce Spatio-Temporal Deep Graph Infomax (STDGI)---a fully unsupervised node representation learning approach based on mutual information maximization that exploits both the temporal and spatial dynamics of the graph. Our model tackles the challenging task of node-level regression by training embeddings to maximize the mutual information between patches of the graph, at any giv","authors_text":"Aaron Solomon, C\\u{a}t\\u{a}lina Cangea, Felix L. Opolka, Petar Veli\\v{c}kovi\\'c, Pietro Li\\`o, R Devon Hjelm","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-12T16:47:30Z","title":"Spatio-Temporal Deep Graph Infomax"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.06316","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":"sha256:99f294c74df855cc2b136a3c61123a16812ac5b329eec6083a5055c2228bdd00","target":"record","created_at":"2026-05-17T23:48:43Z","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":"fe242f4629f1cc57a088c08ddaec0cd39b8dfe272236990116705cbff6fb6d04","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-12T16:47:30Z","title_canon_sha256":"ce46d2bd73cfa8a262c9cb87b6d686170c9d8343bd10f95d0ab2d20ec1f370c1"},"schema_version":"1.0","source":{"id":"1904.06316","kind":"arxiv","version":1}},"canonical_sha256":"8dee1fbe20092fb7f50dfc155e4c69ba042c0e94b8923ed9d0ff94034cbb6ec0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8dee1fbe20092fb7f50dfc155e4c69ba042c0e94b8923ed9d0ff94034cbb6ec0","first_computed_at":"2026-05-17T23:48:43.603558Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:43.603558Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2MNTtQl0xHR7kehd2FpPWMYYWsNEisZfw3OOXruoursPI3OE05IhctJ94Sp7Qp2bj1lB8sgVMC4GiHO+MpMaCw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:43.604046Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.06316","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:99f294c74df855cc2b136a3c61123a16812ac5b329eec6083a5055c2228bdd00","sha256:b5623d538165fff855e22ec7c9c3b09efafd9020974e039f34e5df286b563fb4"],"state_sha256":"564766814ff204d2b957a60659797bafc29fce6af0a2a6e9603bf0b411d71237"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NPRQlTh+BoquVZriDuzdGAO8N/79JSGRjLPc+W6O2eBLz25zF0MqYtwh4OAkK6fivh+0vXIbuaui3t5lqsPACw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T19:25:11.656373Z","bundle_sha256":"1fef581c97ec853791298bba0059b4c9608d591254758e71c0480178bec4fb2a"}}