{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:JCUKMKL7YRR6PTSZPV36MJXBQA","short_pith_number":"pith:JCUKMKL7","canonical_record":{"source":{"id":"1710.03015","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2017-10-09T10:04:29Z","cross_cats_sorted":[],"title_canon_sha256":"25da4321be8f23f80cb81a5fd20071a8538b660c1bbcc00db0b07fa17e2efc91","abstract_canon_sha256":"4a487103338ab28e3f623a8260f0afc3465b0c8010ec9902149c465e42df8a7d"},"schema_version":"1.0"},"canonical_sha256":"48a8a6297fc463e7ce597d77e626e18023eb2e9a6f1c1f0bff8e2422dfe03f94","source":{"kind":"arxiv","id":"1710.03015","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.03015","created_at":"2026-05-18T00:18:04Z"},{"alias_kind":"arxiv_version","alias_value":"1710.03015v2","created_at":"2026-05-18T00:18:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.03015","created_at":"2026-05-18T00:18:04Z"},{"alias_kind":"pith_short_12","alias_value":"JCUKMKL7YRR6","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_16","alias_value":"JCUKMKL7YRR6PTSZ","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_8","alias_value":"JCUKMKL7","created_at":"2026-05-18T12:31:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:JCUKMKL7YRR6PTSZPV36MJXBQA","target":"record","payload":{"canonical_record":{"source":{"id":"1710.03015","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2017-10-09T10:04:29Z","cross_cats_sorted":[],"title_canon_sha256":"25da4321be8f23f80cb81a5fd20071a8538b660c1bbcc00db0b07fa17e2efc91","abstract_canon_sha256":"4a487103338ab28e3f623a8260f0afc3465b0c8010ec9902149c465e42df8a7d"},"schema_version":"1.0"},"canonical_sha256":"48a8a6297fc463e7ce597d77e626e18023eb2e9a6f1c1f0bff8e2422dfe03f94","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:18:04.010681Z","signature_b64":"P8xnJODqyKRjgabwPvsI53Fe3zAwWYu3UKHjaZRY4wISQ/RXXTHoB/0nEjYYW1GiBJUTfR+LQE6UupftiQn0Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"48a8a6297fc463e7ce597d77e626e18023eb2e9a6f1c1f0bff8e2422dfe03f94","last_reissued_at":"2026-05-18T00:18:04.010203Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:18:04.010203Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1710.03015","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":"2026-05-18T00:18:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1Uwm2tMsalar4IklzQ2wQUPX5OQnOq6dS9raW3MnuZhB6VZqV/wKg9Qv4BRVGuW8FwVVg9AONnKjgUy3sclODA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-23T18:12:35.591346Z"},"content_sha256":"a0e8e94f0db531d54630d88c0ab5bfacb8ec2190c803166380632c4cfb17b5b9","schema_version":"1.0","event_id":"sha256:a0e8e94f0db531d54630d88c0ab5bfacb8ec2190c803166380632c4cfb17b5b9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:JCUKMKL7YRR6PTSZPV36MJXBQA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Nonlocal Myriad Filters for Cauchy Noise Removal","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.NA","authors_text":"Fabien Pierre, Friederike Laus, Gabriele Steidl","submitted_at":"2017-10-09T10:04:29Z","abstract_excerpt":"The contribution of this paper is two-fold. First, we introduce a generalized myriad filter, which is a method to compute the joint maximum likelihood estimator of the location and the scale parameter of the Cauchy distribution. Estimating only the location parameter is known as myriad filter. We propose an efficient algorithm to compute the generalized myriad filter and prove its convergence. Special cases of this algorithm result in the classical myriad filtering, respective an algorithm for estimating only the scale parameter. Based on an asymptotic analysis, we develop a second, even faste"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.03015","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":"2026-05-18T00:18:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cwVTTBnArqVsBJ+9B/ybdOjuFuAWdWsh5kQmybMsxb+ry9qPOdQhXVOjOBXy3SSu+ji1y/Ru41CVzljA57WtBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-23T18:12:35.591689Z"},"content_sha256":"2e0f04d048155e8b4bfb37fc3b339d2f58c52967132ec6653e2bbf44caa33926","schema_version":"1.0","event_id":"sha256:2e0f04d048155e8b4bfb37fc3b339d2f58c52967132ec6653e2bbf44caa33926"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JCUKMKL7YRR6PTSZPV36MJXBQA/bundle.json","state_url":"https://pith.science/pith/JCUKMKL7YRR6PTSZPV36MJXBQA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JCUKMKL7YRR6PTSZPV36MJXBQA/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":"2026-06-23T18:12:35Z","links":{"resolver":"https://pith.science/pith/JCUKMKL7YRR6PTSZPV36MJXBQA","bundle":"https://pith.science/pith/JCUKMKL7YRR6PTSZPV36MJXBQA/bundle.json","state":"https://pith.science/pith/JCUKMKL7YRR6PTSZPV36MJXBQA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JCUKMKL7YRR6PTSZPV36MJXBQA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:JCUKMKL7YRR6PTSZPV36MJXBQA","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":"4a487103338ab28e3f623a8260f0afc3465b0c8010ec9902149c465e42df8a7d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2017-10-09T10:04:29Z","title_canon_sha256":"25da4321be8f23f80cb81a5fd20071a8538b660c1bbcc00db0b07fa17e2efc91"},"schema_version":"1.0","source":{"id":"1710.03015","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.03015","created_at":"2026-05-18T00:18:04Z"},{"alias_kind":"arxiv_version","alias_value":"1710.03015v2","created_at":"2026-05-18T00:18:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.03015","created_at":"2026-05-18T00:18:04Z"},{"alias_kind":"pith_short_12","alias_value":"JCUKMKL7YRR6","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_16","alias_value":"JCUKMKL7YRR6PTSZ","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_8","alias_value":"JCUKMKL7","created_at":"2026-05-18T12:31:21Z"}],"graph_snapshots":[{"event_id":"sha256:2e0f04d048155e8b4bfb37fc3b339d2f58c52967132ec6653e2bbf44caa33926","target":"graph","created_at":"2026-05-18T00:18:04Z","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":"The contribution of this paper is two-fold. First, we introduce a generalized myriad filter, which is a method to compute the joint maximum likelihood estimator of the location and the scale parameter of the Cauchy distribution. Estimating only the location parameter is known as myriad filter. We propose an efficient algorithm to compute the generalized myriad filter and prove its convergence. Special cases of this algorithm result in the classical myriad filtering, respective an algorithm for estimating only the scale parameter. Based on an asymptotic analysis, we develop a second, even faste","authors_text":"Fabien Pierre, Friederike Laus, Gabriele Steidl","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2017-10-09T10:04:29Z","title":"Nonlocal Myriad Filters for Cauchy Noise Removal"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.03015","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:a0e8e94f0db531d54630d88c0ab5bfacb8ec2190c803166380632c4cfb17b5b9","target":"record","created_at":"2026-05-18T00:18:04Z","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":"4a487103338ab28e3f623a8260f0afc3465b0c8010ec9902149c465e42df8a7d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2017-10-09T10:04:29Z","title_canon_sha256":"25da4321be8f23f80cb81a5fd20071a8538b660c1bbcc00db0b07fa17e2efc91"},"schema_version":"1.0","source":{"id":"1710.03015","kind":"arxiv","version":2}},"canonical_sha256":"48a8a6297fc463e7ce597d77e626e18023eb2e9a6f1c1f0bff8e2422dfe03f94","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"48a8a6297fc463e7ce597d77e626e18023eb2e9a6f1c1f0bff8e2422dfe03f94","first_computed_at":"2026-05-18T00:18:04.010203Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:18:04.010203Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"P8xnJODqyKRjgabwPvsI53Fe3zAwWYu3UKHjaZRY4wISQ/RXXTHoB/0nEjYYW1GiBJUTfR+LQE6UupftiQn0Bw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:18:04.010681Z","signed_message":"canonical_sha256_bytes"},"source_id":"1710.03015","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a0e8e94f0db531d54630d88c0ab5bfacb8ec2190c803166380632c4cfb17b5b9","sha256:2e0f04d048155e8b4bfb37fc3b339d2f58c52967132ec6653e2bbf44caa33926"],"state_sha256":"a9d9c36766f6d527e036811f113169d51641e02e0b3d1cbb7155292a5b4d65ac"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"isbpzbCAcGKVpvGDpGFFGU4SktUT0MbuXI3CZdO+N8NC4qLVhPQRq4i95Trgt0UThlYEruXTnM8cqsKqqEqjBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-23T18:12:35.593786Z","bundle_sha256":"4ef6ddce543c1e134a195f1f1142bed3082e3190096c6acaf8d84062969141d2"}}