{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:WKJ54TK6Y7TZWD7WLBOPHKG7FU","short_pith_number":"pith:WKJ54TK6","canonical_record":{"source":{"id":"2207.01437","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-07-04T14:25:12Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"ff42139ff999e4013f288f014b49788f8dd2124c6b21fb9b6b9a54fd76b54f20","abstract_canon_sha256":"a688575e7d85d131b96917d4e567ad88c03e48710c49a0a609a2ec4370fb57eb"},"schema_version":"1.0"},"canonical_sha256":"b293de4d5ec7e79b0ff6585cf3a8df2d237658c03a16672c15f8d456345d46b4","source":{"kind":"arxiv","id":"2207.01437","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.01437","created_at":"2026-07-05T04:37:11Z"},{"alias_kind":"arxiv_version","alias_value":"2207.01437v1","created_at":"2026-07-05T04:37:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.01437","created_at":"2026-07-05T04:37:11Z"},{"alias_kind":"pith_short_12","alias_value":"WKJ54TK6Y7TZ","created_at":"2026-07-05T04:37:11Z"},{"alias_kind":"pith_short_16","alias_value":"WKJ54TK6Y7TZWD7W","created_at":"2026-07-05T04:37:11Z"},{"alias_kind":"pith_short_8","alias_value":"WKJ54TK6","created_at":"2026-07-05T04:37:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:WKJ54TK6Y7TZWD7WLBOPHKG7FU","target":"record","payload":{"canonical_record":{"source":{"id":"2207.01437","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-07-04T14:25:12Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"ff42139ff999e4013f288f014b49788f8dd2124c6b21fb9b6b9a54fd76b54f20","abstract_canon_sha256":"a688575e7d85d131b96917d4e567ad88c03e48710c49a0a609a2ec4370fb57eb"},"schema_version":"1.0"},"canonical_sha256":"b293de4d5ec7e79b0ff6585cf3a8df2d237658c03a16672c15f8d456345d46b4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:37:11.936694Z","signature_b64":"ChFAbFqwoo1fbdce+l9fVbNqaUbERDZjLCiE1+YmAq4UvEq5kN1WSpdqGZXBT0J3sQI9vh2hw4B19Lu3aJjaDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b293de4d5ec7e79b0ff6585cf3a8df2d237658c03a16672c15f8d456345d46b4","last_reissued_at":"2026-07-05T04:37:11.936286Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:37:11.936286Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.01437","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":"2026-07-05T04:37:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8T37L/o9ZuXV7miPAMP2Z74hpDAQClAOhTjE0cVlArOqmb4K44b2ABC4G323vCEPHlce9DaGoKfnTH4E9U1LCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T13:30:11.289893Z"},"content_sha256":"5f5bec2d3c6e38ef85832e638a950695894649c02cc743cbe846d0ecdb08ef06","schema_version":"1.0","event_id":"sha256:5f5bec2d3c6e38ef85832e638a950695894649c02cc743cbe846d0ecdb08ef06"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:WKJ54TK6Y7TZWD7WLBOPHKG7FU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Representation Learning with Information Theory for COVID-19 Detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Abel D\\'iaz Berenguer, Hichem Sahli, Matias Bossa, Nikos Deligiannis, Tanmoy Mukherjee","submitted_at":"2022-07-04T14:25:12Z","abstract_excerpt":"Successful data representation is a fundamental factor in machine learning based medical imaging analysis. Deep Learning (DL) has taken an essential role in robust representation learning. However, the inability of deep models to generalize to unseen data can quickly overfit intricate patterns. Thereby, we can conveniently implement strategies to aid deep models in discovering useful priors from data to learn their intrinsic properties. Our model, which we call a dual role network (DRN), uses a dependency maximization approach based on Least Squared Mutual Information (LSMI). The LSMI leverage"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.01437","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/2207.01437/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":"2026-07-05T04:37:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kzpxgh9gkg6+rZXk5Ed4JXhOy2pndH8gdgTJXq1fLoVB+efSpanz1CRLbnDEb//4C4PL0gyV9MQfLGbfjf/QBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T13:30:11.290434Z"},"content_sha256":"a3c8cb213cb06b9e15ccbeadcf87837d34f8b8530abee35bd3df900a6211ef08","schema_version":"1.0","event_id":"sha256:a3c8cb213cb06b9e15ccbeadcf87837d34f8b8530abee35bd3df900a6211ef08"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WKJ54TK6Y7TZWD7WLBOPHKG7FU/bundle.json","state_url":"https://pith.science/pith/WKJ54TK6Y7TZWD7WLBOPHKG7FU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WKJ54TK6Y7TZWD7WLBOPHKG7FU/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":"2026-08-06T13:30:11Z","links":{"resolver":"https://pith.science/pith/WKJ54TK6Y7TZWD7WLBOPHKG7FU","bundle":"https://pith.science/pith/WKJ54TK6Y7TZWD7WLBOPHKG7FU/bundle.json","state":"https://pith.science/pith/WKJ54TK6Y7TZWD7WLBOPHKG7FU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WKJ54TK6Y7TZWD7WLBOPHKG7FU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:WKJ54TK6Y7TZWD7WLBOPHKG7FU","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":"a688575e7d85d131b96917d4e567ad88c03e48710c49a0a609a2ec4370fb57eb","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-07-04T14:25:12Z","title_canon_sha256":"ff42139ff999e4013f288f014b49788f8dd2124c6b21fb9b6b9a54fd76b54f20"},"schema_version":"1.0","source":{"id":"2207.01437","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.01437","created_at":"2026-07-05T04:37:11Z"},{"alias_kind":"arxiv_version","alias_value":"2207.01437v1","created_at":"2026-07-05T04:37:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.01437","created_at":"2026-07-05T04:37:11Z"},{"alias_kind":"pith_short_12","alias_value":"WKJ54TK6Y7TZ","created_at":"2026-07-05T04:37:11Z"},{"alias_kind":"pith_short_16","alias_value":"WKJ54TK6Y7TZWD7W","created_at":"2026-07-05T04:37:11Z"},{"alias_kind":"pith_short_8","alias_value":"WKJ54TK6","created_at":"2026-07-05T04:37:11Z"}],"graph_snapshots":[{"event_id":"sha256:a3c8cb213cb06b9e15ccbeadcf87837d34f8b8530abee35bd3df900a6211ef08","target":"graph","created_at":"2026-07-05T04:37:11Z","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/2207.01437/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Successful data representation is a fundamental factor in machine learning based medical imaging analysis. Deep Learning (DL) has taken an essential role in robust representation learning. However, the inability of deep models to generalize to unseen data can quickly overfit intricate patterns. Thereby, we can conveniently implement strategies to aid deep models in discovering useful priors from data to learn their intrinsic properties. Our model, which we call a dual role network (DRN), uses a dependency maximization approach based on Least Squared Mutual Information (LSMI). The LSMI leverage","authors_text":"Abel D\\'iaz Berenguer, Hichem Sahli, Matias Bossa, Nikos Deligiannis, Tanmoy Mukherjee","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-07-04T14:25:12Z","title":"Representation Learning with Information Theory for COVID-19 Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.01437","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":"sha256:5f5bec2d3c6e38ef85832e638a950695894649c02cc743cbe846d0ecdb08ef06","target":"record","created_at":"2026-07-05T04:37:11Z","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":"a688575e7d85d131b96917d4e567ad88c03e48710c49a0a609a2ec4370fb57eb","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-07-04T14:25:12Z","title_canon_sha256":"ff42139ff999e4013f288f014b49788f8dd2124c6b21fb9b6b9a54fd76b54f20"},"schema_version":"1.0","source":{"id":"2207.01437","kind":"arxiv","version":1}},"canonical_sha256":"b293de4d5ec7e79b0ff6585cf3a8df2d237658c03a16672c15f8d456345d46b4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b293de4d5ec7e79b0ff6585cf3a8df2d237658c03a16672c15f8d456345d46b4","first_computed_at":"2026-07-05T04:37:11.936286Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:37:11.936286Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ChFAbFqwoo1fbdce+l9fVbNqaUbERDZjLCiE1+YmAq4UvEq5kN1WSpdqGZXBT0J3sQI9vh2hw4B19Lu3aJjaDA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:37:11.936694Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.01437","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5f5bec2d3c6e38ef85832e638a950695894649c02cc743cbe846d0ecdb08ef06","sha256:a3c8cb213cb06b9e15ccbeadcf87837d34f8b8530abee35bd3df900a6211ef08"],"state_sha256":"1e9306ca55dc898863ac4037e707b68f2e8b7f9e1acc4b4db2b5181fd34a2ad4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xPnyLJG1S6uLKOjnR0FgxdvZhyMtP9eODw5EqReP9BI/Z9otSSuJ/TPApE/sdYYD0xZj4p0U+7+NGK43HdO/CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T13:30:11.296683Z","bundle_sha256":"4824df910a1e0d2884f6dd0a0d9dad11817871799c2dac73ccf54985a3b88424"}}