{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:U22SXADFWKBQITE3UY44SJN5UU","short_pith_number":"pith:U22SXADF","canonical_record":{"source":{"id":"2102.02485","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-02-04T08:52:46Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"ffef398e81e4fa16151d09ecc157d657b82eebbb9da9658d811f25db9012c476","abstract_canon_sha256":"3fec01964c26be7c69e51a8e8d7da7dfba56fc26548d08aa750e4ba449204b2c"},"schema_version":"1.0"},"canonical_sha256":"a6b52b8065b283044c9ba639c925bda51923c2825c87fddb05cdf15d5e13be65","source":{"kind":"arxiv","id":"2102.02485","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.02485","created_at":"2026-07-05T02:12:49Z"},{"alias_kind":"arxiv_version","alias_value":"2102.02485v1","created_at":"2026-07-05T02:12:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.02485","created_at":"2026-07-05T02:12:49Z"},{"alias_kind":"pith_short_12","alias_value":"U22SXADFWKBQ","created_at":"2026-07-05T02:12:49Z"},{"alias_kind":"pith_short_16","alias_value":"U22SXADFWKBQITE3","created_at":"2026-07-05T02:12:49Z"},{"alias_kind":"pith_short_8","alias_value":"U22SXADF","created_at":"2026-07-05T02:12:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:U22SXADFWKBQITE3UY44SJN5UU","target":"record","payload":{"canonical_record":{"source":{"id":"2102.02485","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-02-04T08:52:46Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"ffef398e81e4fa16151d09ecc157d657b82eebbb9da9658d811f25db9012c476","abstract_canon_sha256":"3fec01964c26be7c69e51a8e8d7da7dfba56fc26548d08aa750e4ba449204b2c"},"schema_version":"1.0"},"canonical_sha256":"a6b52b8065b283044c9ba639c925bda51923c2825c87fddb05cdf15d5e13be65","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:12:49.056569Z","signature_b64":"aYyNRmrIoNFpbYLvCRnO6LB8Xs0PPWRavra+DlwZhr2Zi2ZCcbjKVB+PnNweoIn/B/uk3gA3on72PKAKpqUmCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a6b52b8065b283044c9ba639c925bda51923c2825c87fddb05cdf15d5e13be65","last_reissued_at":"2026-07-05T02:12:49.056144Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:12:49.056144Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2102.02485","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":"2026-07-05T02:12:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X6dyN4RJhwMC83S4Ghhyw3q9+EF8l+IWV6Tyt0Zr4BaBl3sFXiNNGj+jCkybqkgnY0WM8xXPWjWN5th4RnVrAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:08:15.620628Z"},"content_sha256":"0219f49de3f4be94e67c7db1a68b5139323ae86fc5193b72b601ab03bd0d9e5f","schema_version":"1.0","event_id":"sha256:0219f49de3f4be94e67c7db1a68b5139323ae86fc5193b72b601ab03bd0d9e5f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:U22SXADFWKBQITE3UY44SJN5UU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Image Restoration by Deep Projected GSURE","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Raja Giryes, Se Young Chun, Shady Abu-Hussein, Tom Tirer, Yonina C. Eldar","submitted_at":"2021-02-04T08:52:46Z","abstract_excerpt":"Ill-posed inverse problems appear in many image processing applications, such as deblurring and super-resolution. In recent years, solutions that are based on deep Convolutional Neural Networks (CNNs) have shown great promise. Yet, most of these techniques, which train CNNs using external data, are restricted to the observation models that have been used in the training phase. A recent alternative that does not have this drawback relies on learning the target image using internal learning. One such prominent example is the Deep Image Prior (DIP) technique that trains a network directly on the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.02485","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/2102.02485/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":"2026-07-05T02:12:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZV/QFXVHQcUmD7n062njFheqvtaEbeENlwiNBzR5/32aoU7AloscAa3M+zOv1qPOOoznDJMNmqRne82uje+EBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:08:15.621549Z"},"content_sha256":"7d02e11eb8e56b1e39a9e7723c2a7d252133f68637e5779284e5692490284faf","schema_version":"1.0","event_id":"sha256:7d02e11eb8e56b1e39a9e7723c2a7d252133f68637e5779284e5692490284faf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/U22SXADFWKBQITE3UY44SJN5UU/bundle.json","state_url":"https://pith.science/pith/U22SXADFWKBQITE3UY44SJN5UU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/U22SXADFWKBQITE3UY44SJN5UU/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":"2026-08-06T19:08:15Z","links":{"resolver":"https://pith.science/pith/U22SXADFWKBQITE3UY44SJN5UU","bundle":"https://pith.science/pith/U22SXADFWKBQITE3UY44SJN5UU/bundle.json","state":"https://pith.science/pith/U22SXADFWKBQITE3UY44SJN5UU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/U22SXADFWKBQITE3UY44SJN5UU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:U22SXADFWKBQITE3UY44SJN5UU","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":"3fec01964c26be7c69e51a8e8d7da7dfba56fc26548d08aa750e4ba449204b2c","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-02-04T08:52:46Z","title_canon_sha256":"ffef398e81e4fa16151d09ecc157d657b82eebbb9da9658d811f25db9012c476"},"schema_version":"1.0","source":{"id":"2102.02485","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.02485","created_at":"2026-07-05T02:12:49Z"},{"alias_kind":"arxiv_version","alias_value":"2102.02485v1","created_at":"2026-07-05T02:12:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.02485","created_at":"2026-07-05T02:12:49Z"},{"alias_kind":"pith_short_12","alias_value":"U22SXADFWKBQ","created_at":"2026-07-05T02:12:49Z"},{"alias_kind":"pith_short_16","alias_value":"U22SXADFWKBQITE3","created_at":"2026-07-05T02:12:49Z"},{"alias_kind":"pith_short_8","alias_value":"U22SXADF","created_at":"2026-07-05T02:12:49Z"}],"graph_snapshots":[{"event_id":"sha256:7d02e11eb8e56b1e39a9e7723c2a7d252133f68637e5779284e5692490284faf","target":"graph","created_at":"2026-07-05T02:12:49Z","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/2102.02485/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Ill-posed inverse problems appear in many image processing applications, such as deblurring and super-resolution. In recent years, solutions that are based on deep Convolutional Neural Networks (CNNs) have shown great promise. Yet, most of these techniques, which train CNNs using external data, are restricted to the observation models that have been used in the training phase. A recent alternative that does not have this drawback relies on learning the target image using internal learning. One such prominent example is the Deep Image Prior (DIP) technique that trains a network directly on the ","authors_text":"Raja Giryes, Se Young Chun, Shady Abu-Hussein, Tom Tirer, Yonina C. Eldar","cross_cats":["eess.IV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-02-04T08:52:46Z","title":"Image Restoration by Deep Projected GSURE"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.02485","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":"sha256:0219f49de3f4be94e67c7db1a68b5139323ae86fc5193b72b601ab03bd0d9e5f","target":"record","created_at":"2026-07-05T02:12:49Z","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":"3fec01964c26be7c69e51a8e8d7da7dfba56fc26548d08aa750e4ba449204b2c","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-02-04T08:52:46Z","title_canon_sha256":"ffef398e81e4fa16151d09ecc157d657b82eebbb9da9658d811f25db9012c476"},"schema_version":"1.0","source":{"id":"2102.02485","kind":"arxiv","version":1}},"canonical_sha256":"a6b52b8065b283044c9ba639c925bda51923c2825c87fddb05cdf15d5e13be65","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a6b52b8065b283044c9ba639c925bda51923c2825c87fddb05cdf15d5e13be65","first_computed_at":"2026-07-05T02:12:49.056144Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:12:49.056144Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aYyNRmrIoNFpbYLvCRnO6LB8Xs0PPWRavra+DlwZhr2Zi2ZCcbjKVB+PnNweoIn/B/uk3gA3on72PKAKpqUmCw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:12:49.056569Z","signed_message":"canonical_sha256_bytes"},"source_id":"2102.02485","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0219f49de3f4be94e67c7db1a68b5139323ae86fc5193b72b601ab03bd0d9e5f","sha256:7d02e11eb8e56b1e39a9e7723c2a7d252133f68637e5779284e5692490284faf"],"state_sha256":"bf7ac3ace3d388939dccbd49490e5c9634b325cc3363252ef5cb197ea76e958f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2fpRLQ7HQKQCL9lY3nOd7TfNoSQqq8vMTMahhmKdBd/KATEPmPsCF2IEK19Mb3bMlK1N+/uwuU/Qs+mIqm0TDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T19:08:15.628180Z","bundle_sha256":"94966d0e36ec69bc03a018cbcaa970c2bbebc791a1c99fdbd0ce5c8c184f006b"}}