{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:NMVRKHUQYYDOV7MB7YRM7DJDLS","short_pith_number":"pith:NMVRKHUQ","canonical_record":{"source":{"id":"2409.08760","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-09-13T12:09:09Z","cross_cats_sorted":["eess.SP"],"title_canon_sha256":"52835faa6826efd65fb2df95b0f7dabaf7fbead6ad620b76b7c0355385f3a654","abstract_canon_sha256":"b268aa3d29de29835f51e77e696e38c1395362b83293b1761af27b7dd4170824"},"schema_version":"1.0"},"canonical_sha256":"6b2b151e90c606eafd81fe22cf8d235c91b63b4994c75b6390498000d7b47e0a","source":{"kind":"arxiv","id":"2409.08760","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.08760","created_at":"2026-07-05T09:06:46Z"},{"alias_kind":"arxiv_version","alias_value":"2409.08760v1","created_at":"2026-07-05T09:06:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.08760","created_at":"2026-07-05T09:06:46Z"},{"alias_kind":"pith_short_12","alias_value":"NMVRKHUQYYDO","created_at":"2026-07-05T09:06:46Z"},{"alias_kind":"pith_short_16","alias_value":"NMVRKHUQYYDOV7MB","created_at":"2026-07-05T09:06:46Z"},{"alias_kind":"pith_short_8","alias_value":"NMVRKHUQ","created_at":"2026-07-05T09:06:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:NMVRKHUQYYDOV7MB7YRM7DJDLS","target":"record","payload":{"canonical_record":{"source":{"id":"2409.08760","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-09-13T12:09:09Z","cross_cats_sorted":["eess.SP"],"title_canon_sha256":"52835faa6826efd65fb2df95b0f7dabaf7fbead6ad620b76b7c0355385f3a654","abstract_canon_sha256":"b268aa3d29de29835f51e77e696e38c1395362b83293b1761af27b7dd4170824"},"schema_version":"1.0"},"canonical_sha256":"6b2b151e90c606eafd81fe22cf8d235c91b63b4994c75b6390498000d7b47e0a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:06:46.838969Z","signature_b64":"FKUnYcA9bak5jCk6PZe8LcfnNCstrvrZHfJKO9cJ7SUS5BBH/E60PR3YQWisDnrRVdZ+v7Px+DBkqZ+KUEIMAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6b2b151e90c606eafd81fe22cf8d235c91b63b4994c75b6390498000d7b47e0a","last_reissued_at":"2026-07-05T09:06:46.838509Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:06:46.838509Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.08760","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":"2026-07-05T09:06:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y0VyDawk6XRECxM0c1kvGZ84zGkW9LowuzXMXx4Wv8wdR/nntqM1j+z1c79btbquYF235WQFxikqZJhG4PKBBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T10:04:32.008783Z"},"content_sha256":"4315c16a11847cc43ceda3d2fadb6433adc9dba181506ef0f938d6bf743069a4","schema_version":"1.0","event_id":"sha256:4315c16a11847cc43ceda3d2fadb6433adc9dba181506ef0f938d6bf743069a4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:NMVRKHUQYYDOV7MB7YRM7DJDLS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Online Network Inference from Graph-Stationary Signals with Hidden Nodes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["eess.SP"],"primary_cat":"cs.LG","authors_text":"Andrei Buciulea, Antonio G. Marques, Madeline Navarro, Samuel Rey, Santiago Segarra","submitted_at":"2024-09-13T12:09:09Z","abstract_excerpt":"Graph learning is the fundamental task of estimating unknown graph connectivity from available data. Typical approaches assume that not only is all information available simultaneously but also that all nodes can be observed. However, in many real-world scenarios, data can neither be known completely nor obtained all at once. We present a novel method for online graph estimation that accounts for the presence of hidden nodes. We consider signals that are stationary on the underlying graph, which provides a model for the unknown connections to hidden nodes. We then formulate a convex optimizati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.08760","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2409.08760/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":"2026-07-05T09:06:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"46W79l172lxb7W4g2Dj5ng13YbIwDLEz6vIBqr+tKuqqUjMDfIZeq2H1EAL6o/rJId9/xhVbLW20K4qIjPlsDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T10:04:32.009371Z"},"content_sha256":"ddb47d148e9df8739b2a8f35c790f15f0317d821eb080ecede0ab5028bc74da8","schema_version":"1.0","event_id":"sha256:ddb47d148e9df8739b2a8f35c790f15f0317d821eb080ecede0ab5028bc74da8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NMVRKHUQYYDOV7MB7YRM7DJDLS/bundle.json","state_url":"https://pith.science/pith/NMVRKHUQYYDOV7MB7YRM7DJDLS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NMVRKHUQYYDOV7MB7YRM7DJDLS/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":"2026-08-21T10:04:32Z","links":{"resolver":"https://pith.science/pith/NMVRKHUQYYDOV7MB7YRM7DJDLS","bundle":"https://pith.science/pith/NMVRKHUQYYDOV7MB7YRM7DJDLS/bundle.json","state":"https://pith.science/pith/NMVRKHUQYYDOV7MB7YRM7DJDLS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NMVRKHUQYYDOV7MB7YRM7DJDLS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NMVRKHUQYYDOV7MB7YRM7DJDLS","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":"b268aa3d29de29835f51e77e696e38c1395362b83293b1761af27b7dd4170824","cross_cats_sorted":["eess.SP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-09-13T12:09:09Z","title_canon_sha256":"52835faa6826efd65fb2df95b0f7dabaf7fbead6ad620b76b7c0355385f3a654"},"schema_version":"1.0","source":{"id":"2409.08760","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.08760","created_at":"2026-07-05T09:06:46Z"},{"alias_kind":"arxiv_version","alias_value":"2409.08760v1","created_at":"2026-07-05T09:06:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.08760","created_at":"2026-07-05T09:06:46Z"},{"alias_kind":"pith_short_12","alias_value":"NMVRKHUQYYDO","created_at":"2026-07-05T09:06:46Z"},{"alias_kind":"pith_short_16","alias_value":"NMVRKHUQYYDOV7MB","created_at":"2026-07-05T09:06:46Z"},{"alias_kind":"pith_short_8","alias_value":"NMVRKHUQ","created_at":"2026-07-05T09:06:46Z"}],"graph_snapshots":[{"event_id":"sha256:ddb47d148e9df8739b2a8f35c790f15f0317d821eb080ecede0ab5028bc74da8","target":"graph","created_at":"2026-07-05T09:06:46Z","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/2409.08760/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph learning is the fundamental task of estimating unknown graph connectivity from available data. Typical approaches assume that not only is all information available simultaneously but also that all nodes can be observed. However, in many real-world scenarios, data can neither be known completely nor obtained all at once. We present a novel method for online graph estimation that accounts for the presence of hidden nodes. We consider signals that are stationary on the underlying graph, which provides a model for the unknown connections to hidden nodes. We then formulate a convex optimizati","authors_text":"Andrei Buciulea, Antonio G. Marques, Madeline Navarro, Samuel Rey, Santiago Segarra","cross_cats":["eess.SP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-09-13T12:09:09Z","title":"Online Network Inference from Graph-Stationary Signals with Hidden Nodes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.08760","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":"sha256:4315c16a11847cc43ceda3d2fadb6433adc9dba181506ef0f938d6bf743069a4","target":"record","created_at":"2026-07-05T09:06:46Z","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":"b268aa3d29de29835f51e77e696e38c1395362b83293b1761af27b7dd4170824","cross_cats_sorted":["eess.SP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-09-13T12:09:09Z","title_canon_sha256":"52835faa6826efd65fb2df95b0f7dabaf7fbead6ad620b76b7c0355385f3a654"},"schema_version":"1.0","source":{"id":"2409.08760","kind":"arxiv","version":1}},"canonical_sha256":"6b2b151e90c606eafd81fe22cf8d235c91b63b4994c75b6390498000d7b47e0a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6b2b151e90c606eafd81fe22cf8d235c91b63b4994c75b6390498000d7b47e0a","first_computed_at":"2026-07-05T09:06:46.838509Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:06:46.838509Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FKUnYcA9bak5jCk6PZe8LcfnNCstrvrZHfJKO9cJ7SUS5BBH/E60PR3YQWisDnrRVdZ+v7Px+DBkqZ+KUEIMAA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:06:46.838969Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.08760","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4315c16a11847cc43ceda3d2fadb6433adc9dba181506ef0f938d6bf743069a4","sha256:ddb47d148e9df8739b2a8f35c790f15f0317d821eb080ecede0ab5028bc74da8"],"state_sha256":"47f9fc311edf2a5ba47da54fbe1fd606361b404d658b0e84f15bc573c9fbe7f3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V/Br6S9uccOczcw52b4l1Yq51Gud7XCTbifStJy//ujMp44LPsCUUbYfBv02BT2z9CVrPWVu40q5bcqDwiLABA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T10:04:32.013656Z","bundle_sha256":"854958dca63eaae0f177bb63454fb76b0feb1196eb90fb8029da44529d8aa25e"}}