{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:CCZHHVESGO26V2QTSJSYPYD7YL","short_pith_number":"pith:CCZHHVES","canonical_record":{"source":{"id":"1810.09155","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-22T09:47:38Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"260b79bc457df973b795be595065b1726cb0b61be293cc750367504631305a7b","abstract_canon_sha256":"6f3e58f3a062238ce630d2dd1f8eda6cf3537977a20daa69adaba3dfb864f194"},"schema_version":"1.0"},"canonical_sha256":"10b273d49233b5eaea13926587e07fc2c38e2b631622924c7f0eb5b64ed6c1d9","source":{"kind":"arxiv","id":"1810.09155","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.09155","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"arxiv_version","alias_value":"1810.09155v2","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.09155","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"pith_short_12","alias_value":"CCZHHVESGO26","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"CCZHHVESGO26V2QT","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"CCZHHVES","created_at":"2026-05-18T12:32:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:CCZHHVESGO26V2QTSJSYPYD7YL","target":"record","payload":{"canonical_record":{"source":{"id":"1810.09155","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-22T09:47:38Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"260b79bc457df973b795be595065b1726cb0b61be293cc750367504631305a7b","abstract_canon_sha256":"6f3e58f3a062238ce630d2dd1f8eda6cf3537977a20daa69adaba3dfb864f194"},"schema_version":"1.0"},"canonical_sha256":"10b273d49233b5eaea13926587e07fc2c38e2b631622924c7f0eb5b64ed6c1d9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:01:06.629012Z","signature_b64":"xIOFpn2VLpB/kCfEU3rJi43V/BH9ecj7wshtVR9adcdKT3pILN11TEr8tXvwcohM5JXOsRsEoIK42l3IEXObAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"10b273d49233b5eaea13926587e07fc2c38e2b631622924c7f0eb5b64ed6c1d9","last_reissued_at":"2026-05-18T00:01:06.628614Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:01:06.628614Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.09155","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":"2026-05-18T00:01:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i/ejknCFqQ2C/UnPMfII7xox1mNVj+6trqzbpNZKpEiumcGgYn+SCItXBi8bSf0cha0CSMZNC1kig88LNcJlCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T07:16:46.297872Z"},"content_sha256":"cfc4c693ed63f085eef994bfd24198d195b90c1fdb2a73aec7fa6d72240883d5","schema_version":"1.0","event_id":"sha256:cfc4c693ed63f085eef994bfd24198d195b90c1fdb2a73aec7fa6d72240883d5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:CCZHHVESGO26V2QTSJSYPYD7YL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Simple Baseline Algorithm for Graph Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Edouard Pineau, Nathan de Lara","submitted_at":"2018-10-22T09:47:38Z","abstract_excerpt":"Graph classification has recently received a lot of attention from various fields of machine learning e.g. kernel methods, sequential modeling or graph embedding. All these approaches offer promising results with different respective strengths and weaknesses. However, most of them rely on complex mathematics and require heavy computational power to achieve their best performance. We propose a simple and fast algorithm based on the spectral decomposition of graph Laplacian to perform graph classification and get a first reference score for a dataset. We show that this method obtains competitive"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.09155","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":""},"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":"2026-05-18T00:01:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"o9wVefGzx0NMMUth3jz4mmAzcfsnBDZD/RukQYS8Oezchw8Z0v9wbbDa3D7oxIWwYfonXmHXxsBacxvOd8UiBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T07:16:46.298220Z"},"content_sha256":"fcc88ff9c4a894f506241c342a7a9a7154fb5f2617b8ba9aaba8e7e6642b976e","schema_version":"1.0","event_id":"sha256:fcc88ff9c4a894f506241c342a7a9a7154fb5f2617b8ba9aaba8e7e6642b976e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CCZHHVESGO26V2QTSJSYPYD7YL/bundle.json","state_url":"https://pith.science/pith/CCZHHVESGO26V2QTSJSYPYD7YL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CCZHHVESGO26V2QTSJSYPYD7YL/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":"2026-06-25T07:16:46Z","links":{"resolver":"https://pith.science/pith/CCZHHVESGO26V2QTSJSYPYD7YL","bundle":"https://pith.science/pith/CCZHHVESGO26V2QTSJSYPYD7YL/bundle.json","state":"https://pith.science/pith/CCZHHVESGO26V2QTSJSYPYD7YL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CCZHHVESGO26V2QTSJSYPYD7YL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:CCZHHVESGO26V2QTSJSYPYD7YL","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":"6f3e58f3a062238ce630d2dd1f8eda6cf3537977a20daa69adaba3dfb864f194","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-22T09:47:38Z","title_canon_sha256":"260b79bc457df973b795be595065b1726cb0b61be293cc750367504631305a7b"},"schema_version":"1.0","source":{"id":"1810.09155","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.09155","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"arxiv_version","alias_value":"1810.09155v2","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.09155","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"pith_short_12","alias_value":"CCZHHVESGO26","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"CCZHHVESGO26V2QT","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"CCZHHVES","created_at":"2026-05-18T12:32:16Z"}],"graph_snapshots":[{"event_id":"sha256:fcc88ff9c4a894f506241c342a7a9a7154fb5f2617b8ba9aaba8e7e6642b976e","target":"graph","created_at":"2026-05-18T00:01:06Z","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":"Graph classification has recently received a lot of attention from various fields of machine learning e.g. kernel methods, sequential modeling or graph embedding. All these approaches offer promising results with different respective strengths and weaknesses. However, most of them rely on complex mathematics and require heavy computational power to achieve their best performance. We propose a simple and fast algorithm based on the spectral decomposition of graph Laplacian to perform graph classification and get a first reference score for a dataset. We show that this method obtains competitive","authors_text":"Edouard Pineau, Nathan de Lara","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-22T09:47:38Z","title":"A Simple Baseline Algorithm for Graph Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.09155","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:cfc4c693ed63f085eef994bfd24198d195b90c1fdb2a73aec7fa6d72240883d5","target":"record","created_at":"2026-05-18T00:01:06Z","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":"6f3e58f3a062238ce630d2dd1f8eda6cf3537977a20daa69adaba3dfb864f194","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-22T09:47:38Z","title_canon_sha256":"260b79bc457df973b795be595065b1726cb0b61be293cc750367504631305a7b"},"schema_version":"1.0","source":{"id":"1810.09155","kind":"arxiv","version":2}},"canonical_sha256":"10b273d49233b5eaea13926587e07fc2c38e2b631622924c7f0eb5b64ed6c1d9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"10b273d49233b5eaea13926587e07fc2c38e2b631622924c7f0eb5b64ed6c1d9","first_computed_at":"2026-05-18T00:01:06.628614Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:01:06.628614Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xIOFpn2VLpB/kCfEU3rJi43V/BH9ecj7wshtVR9adcdKT3pILN11TEr8tXvwcohM5JXOsRsEoIK42l3IEXObAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:01:06.629012Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.09155","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cfc4c693ed63f085eef994bfd24198d195b90c1fdb2a73aec7fa6d72240883d5","sha256:fcc88ff9c4a894f506241c342a7a9a7154fb5f2617b8ba9aaba8e7e6642b976e"],"state_sha256":"e0e79dee624ffbaccef65ca25d6b9a702e56a397e6a5978f24f6d602a1427b48"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KZr5Kmxj9aChdLcbNzV/epLKgqvjX1EG5KPjFDYNKPmA/oYvqw4AozVPEiD9D3BHaWv+h+nLsLfkkDrbTJVfBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-25T07:16:46.300185Z","bundle_sha256":"e1cca3d3e1e3189c7f327daf4cdc12ef5757b4859fb2734d194c4229fd8a2459"}}