{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:GBSEYRFHCSOT4F3V2WYVZKSTHZ","short_pith_number":"pith:GBSEYRFH","canonical_record":{"source":{"id":"1803.02944","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-03-08T02:39:52Z","cross_cats_sorted":["cs.SI"],"title_canon_sha256":"3e455c284d128f2e2b95143c7dd7d05405149650fd81f8636d055dda445ec2f8","abstract_canon_sha256":"89786c72850ab7031f8a65b1ca5dc381fd59a7c5ea244c93f43116004a07dc4e"},"schema_version":"1.0"},"canonical_sha256":"30644c44a7149d3e1775d5b15caa533e525d2cc4c4c113f85159b612576844a6","source":{"kind":"arxiv","id":"1803.02944","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.02944","created_at":"2026-05-18T00:21:44Z"},{"alias_kind":"arxiv_version","alias_value":"1803.02944v1","created_at":"2026-05-18T00:21:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.02944","created_at":"2026-05-18T00:21:44Z"},{"alias_kind":"pith_short_12","alias_value":"GBSEYRFHCSOT","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GBSEYRFHCSOT4F3V","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GBSEYRFH","created_at":"2026-05-18T12:32:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:GBSEYRFHCSOT4F3V2WYVZKSTHZ","target":"record","payload":{"canonical_record":{"source":{"id":"1803.02944","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-03-08T02:39:52Z","cross_cats_sorted":["cs.SI"],"title_canon_sha256":"3e455c284d128f2e2b95143c7dd7d05405149650fd81f8636d055dda445ec2f8","abstract_canon_sha256":"89786c72850ab7031f8a65b1ca5dc381fd59a7c5ea244c93f43116004a07dc4e"},"schema_version":"1.0"},"canonical_sha256":"30644c44a7149d3e1775d5b15caa533e525d2cc4c4c113f85159b612576844a6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:21:44.924306Z","signature_b64":"OQXY3VDoex1nzAC8fElo7d7LlHe5yAdvLExKP3pW97ZZXhTqQKzeJ4xAz/QMZSAEDW8E3O5FCHPkmoZlmyHjBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"30644c44a7149d3e1775d5b15caa533e525d2cc4c4c113f85159b612576844a6","last_reissued_at":"2026-05-18T00:21:44.923777Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:21:44.923777Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1803.02944","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":"2026-05-18T00:21:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"H35a8/uxDU7PfPYOWvj2mBRmQkqBgrRwYkzhzTz8z/cCS420c7GrNe6GkF89jEcTf7Y5pm9iGvRJ1+hPkta8Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T22:29:17.036061Z"},"content_sha256":"be5b6ecce94d9fa09c746ced9889de06b17f9c3f079b22cb20297a11cd7476da","schema_version":"1.0","event_id":"sha256:be5b6ecce94d9fa09c746ced9889de06b17f9c3f079b22cb20297a11cd7476da"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:GBSEYRFHCSOT4F3V2WYVZKSTHZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multiresolution Representations for Piecewise-Smooth Signals on Graphs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SI"],"primary_cat":"eess.SP","authors_text":"Aarti Singh, Jelena Kova\\v{c}evi\\'c, Siheng Chen","submitted_at":"2018-03-08T02:39:52Z","abstract_excerpt":"What is a mathematically rigorous way to describe the taxi-pickup distribution in Manhattan, or the profile information in online social networks? A deep understanding of representing those data not only provides insights to the data properties, but also benefits to many subsequent processing procedures, such as denoising, sampling, recovery and localization. In this paper, we model those complex and irregular data as piecewise-smooth graph signals and propose a graph dictionary to effectively represent those graph signals. We first propose the graph multiresolution analysis, which provides a "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.02944","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":"2026-05-18T00:21:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZbY6cRuZhcSw36ajRB2UnHZELXsN/TXrwTsfuitvBaH6+yzCRCZmKbxRRU9xuOW4EPgPkjsdAi13EUkkw6lwBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T22:29:17.036766Z"},"content_sha256":"c697c7af45dd4f936f881432f913fe0644ffb3ea850119bacbd3773979c370fa","schema_version":"1.0","event_id":"sha256:c697c7af45dd4f936f881432f913fe0644ffb3ea850119bacbd3773979c370fa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GBSEYRFHCSOT4F3V2WYVZKSTHZ/bundle.json","state_url":"https://pith.science/pith/GBSEYRFHCSOT4F3V2WYVZKSTHZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GBSEYRFHCSOT4F3V2WYVZKSTHZ/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":"2026-05-26T22:29:17Z","links":{"resolver":"https://pith.science/pith/GBSEYRFHCSOT4F3V2WYVZKSTHZ","bundle":"https://pith.science/pith/GBSEYRFHCSOT4F3V2WYVZKSTHZ/bundle.json","state":"https://pith.science/pith/GBSEYRFHCSOT4F3V2WYVZKSTHZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GBSEYRFHCSOT4F3V2WYVZKSTHZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:GBSEYRFHCSOT4F3V2WYVZKSTHZ","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":"89786c72850ab7031f8a65b1ca5dc381fd59a7c5ea244c93f43116004a07dc4e","cross_cats_sorted":["cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-03-08T02:39:52Z","title_canon_sha256":"3e455c284d128f2e2b95143c7dd7d05405149650fd81f8636d055dda445ec2f8"},"schema_version":"1.0","source":{"id":"1803.02944","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.02944","created_at":"2026-05-18T00:21:44Z"},{"alias_kind":"arxiv_version","alias_value":"1803.02944v1","created_at":"2026-05-18T00:21:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.02944","created_at":"2026-05-18T00:21:44Z"},{"alias_kind":"pith_short_12","alias_value":"GBSEYRFHCSOT","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GBSEYRFHCSOT4F3V","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GBSEYRFH","created_at":"2026-05-18T12:32:25Z"}],"graph_snapshots":[{"event_id":"sha256:c697c7af45dd4f936f881432f913fe0644ffb3ea850119bacbd3773979c370fa","target":"graph","created_at":"2026-05-18T00:21:44Z","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":"What is a mathematically rigorous way to describe the taxi-pickup distribution in Manhattan, or the profile information in online social networks? A deep understanding of representing those data not only provides insights to the data properties, but also benefits to many subsequent processing procedures, such as denoising, sampling, recovery and localization. In this paper, we model those complex and irregular data as piecewise-smooth graph signals and propose a graph dictionary to effectively represent those graph signals. We first propose the graph multiresolution analysis, which provides a ","authors_text":"Aarti Singh, Jelena Kova\\v{c}evi\\'c, Siheng Chen","cross_cats":["cs.SI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-03-08T02:39:52Z","title":"Multiresolution Representations for Piecewise-Smooth Signals on Graphs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.02944","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:be5b6ecce94d9fa09c746ced9889de06b17f9c3f079b22cb20297a11cd7476da","target":"record","created_at":"2026-05-18T00:21:44Z","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":"89786c72850ab7031f8a65b1ca5dc381fd59a7c5ea244c93f43116004a07dc4e","cross_cats_sorted":["cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2018-03-08T02:39:52Z","title_canon_sha256":"3e455c284d128f2e2b95143c7dd7d05405149650fd81f8636d055dda445ec2f8"},"schema_version":"1.0","source":{"id":"1803.02944","kind":"arxiv","version":1}},"canonical_sha256":"30644c44a7149d3e1775d5b15caa533e525d2cc4c4c113f85159b612576844a6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"30644c44a7149d3e1775d5b15caa533e525d2cc4c4c113f85159b612576844a6","first_computed_at":"2026-05-18T00:21:44.923777Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:21:44.923777Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OQXY3VDoex1nzAC8fElo7d7LlHe5yAdvLExKP3pW97ZZXhTqQKzeJ4xAz/QMZSAEDW8E3O5FCHPkmoZlmyHjBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:21:44.924306Z","signed_message":"canonical_sha256_bytes"},"source_id":"1803.02944","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:be5b6ecce94d9fa09c746ced9889de06b17f9c3f079b22cb20297a11cd7476da","sha256:c697c7af45dd4f936f881432f913fe0644ffb3ea850119bacbd3773979c370fa"],"state_sha256":"9f7ee56d2480dd1a801535c2e172132ac99248519e75faaca9954f1ff7444447"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2A09FcBpXXWjaDgEss+uR5AhmKVbJB6o2iPgbLS190+r7JC6S5jzRZFU5BSBBULpkhT11bP3cAxX2bb37/h6DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T22:29:17.040441Z","bundle_sha256":"7061848cceec7372eca848f4814bb617c0f6def78137e43c098dd3a48c53bb93"}}