{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:XOGM2ZHZ6L5OFC4UPU4PSSVT4P","short_pith_number":"pith:XOGM2ZHZ","canonical_record":{"source":{"id":"1301.6265","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2013-01-26T16:20:46Z","cross_cats_sorted":["cs.IT","math.IT"],"title_canon_sha256":"4925444dcff528e62901f8043b100389caebd663589deb8fe42d6b04a25a18d7","abstract_canon_sha256":"62937bb57a94061e5e5854bd65df77a3c52572c69e36a36afabb4db52b2b38fd"},"schema_version":"1.0"},"canonical_sha256":"bb8ccd64f9f2fae28b947d38f94ab3e3cf04f66d37ff6253ee2c0302431ea94d","source":{"kind":"arxiv","id":"1301.6265","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.6265","created_at":"2026-05-18T03:22:05Z"},{"alias_kind":"arxiv_version","alias_value":"1301.6265v4","created_at":"2026-05-18T03:22:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.6265","created_at":"2026-05-18T03:22:05Z"},{"alias_kind":"pith_short_12","alias_value":"XOGM2ZHZ6L5O","created_at":"2026-05-18T12:28:06Z"},{"alias_kind":"pith_short_16","alias_value":"XOGM2ZHZ6L5OFC4U","created_at":"2026-05-18T12:28:06Z"},{"alias_kind":"pith_short_8","alias_value":"XOGM2ZHZ","created_at":"2026-05-18T12:28:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:XOGM2ZHZ6L5OFC4UPU4PSSVT4P","target":"record","payload":{"canonical_record":{"source":{"id":"1301.6265","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2013-01-26T16:20:46Z","cross_cats_sorted":["cs.IT","math.IT"],"title_canon_sha256":"4925444dcff528e62901f8043b100389caebd663589deb8fe42d6b04a25a18d7","abstract_canon_sha256":"62937bb57a94061e5e5854bd65df77a3c52572c69e36a36afabb4db52b2b38fd"},"schema_version":"1.0"},"canonical_sha256":"bb8ccd64f9f2fae28b947d38f94ab3e3cf04f66d37ff6253ee2c0302431ea94d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:22:05.602215Z","signature_b64":"nQuK4veQGEoyWQ8jgAmJbi+O0ybm21n69d+u1JD4NlbirnUgSUY1JKQnu4KPLRdPF0ybUafkCiBEgxuTzC0VAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bb8ccd64f9f2fae28b947d38f94ab3e3cf04f66d37ff6253ee2c0302431ea94d","last_reissued_at":"2026-05-18T03:22:05.601390Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:22:05.601390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1301.6265","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:22:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GIgxcU1JXEE66AxoA4JEr8hLBboie3JAD/gDZPqtlTWAjZKWoKF20s+91XFEn3mLKAdVjnf2sQ81Vx2/3SMaCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T19:56:01.615458Z"},"content_sha256":"9ac16da20893aced0334961ba8a94e7b1434381d7e2cb8b83a90ae08881f9aa1","schema_version":"1.0","event_id":"sha256:9ac16da20893aced0334961ba8a94e7b1434381d7e2cb8b83a90ae08881f9aa1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:XOGM2ZHZ6L5OFC4UPU4PSSVT4P","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural Networks Built from Unreliable Components","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","math.IT"],"primary_cat":"cs.NE","authors_text":"Amin Karbasi, Amin Shokrollahi, Amir Hesam Salavati, Lav Varshney","submitted_at":"2013-01-26T16:20:46Z","abstract_excerpt":"Recent advances in associative memory design through strutured pattern sets and graph-based inference algorithms have allowed the reliable learning and retrieval of an exponential number of patterns. Both these and classical associative memories, however, have assumed internally noiseless computational nodes. This paper considers the setting when internal computations are also noisy. Even if all components are noisy, the final error probability in recall can often be made exceedingly small, as we characterize. There is a threshold phenomenon. We also show how to optimize inference algorithm pa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.6265","kind":"arxiv","version":4},"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":"2026-05-18T03:22:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UHVf3xAQCXRyDR47muPu0A9Q5CTXDT4KFht1jLxjnl5xsM1QhCRNz/ZgxmAWH19Wue9vFaBlBSXBKVplvuNGCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T19:56:01.615812Z"},"content_sha256":"a2f1122d5c66237f7e79a9852e89799f485334f980653da8325908c5ed6a872e","schema_version":"1.0","event_id":"sha256:a2f1122d5c66237f7e79a9852e89799f485334f980653da8325908c5ed6a872e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XOGM2ZHZ6L5OFC4UPU4PSSVT4P/bundle.json","state_url":"https://pith.science/pith/XOGM2ZHZ6L5OFC4UPU4PSSVT4P/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XOGM2ZHZ6L5OFC4UPU4PSSVT4P/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":"2026-06-03T19:56:01Z","links":{"resolver":"https://pith.science/pith/XOGM2ZHZ6L5OFC4UPU4PSSVT4P","bundle":"https://pith.science/pith/XOGM2ZHZ6L5OFC4UPU4PSSVT4P/bundle.json","state":"https://pith.science/pith/XOGM2ZHZ6L5OFC4UPU4PSSVT4P/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XOGM2ZHZ6L5OFC4UPU4PSSVT4P/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:XOGM2ZHZ6L5OFC4UPU4PSSVT4P","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":"62937bb57a94061e5e5854bd65df77a3c52572c69e36a36afabb4db52b2b38fd","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2013-01-26T16:20:46Z","title_canon_sha256":"4925444dcff528e62901f8043b100389caebd663589deb8fe42d6b04a25a18d7"},"schema_version":"1.0","source":{"id":"1301.6265","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.6265","created_at":"2026-05-18T03:22:05Z"},{"alias_kind":"arxiv_version","alias_value":"1301.6265v4","created_at":"2026-05-18T03:22:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.6265","created_at":"2026-05-18T03:22:05Z"},{"alias_kind":"pith_short_12","alias_value":"XOGM2ZHZ6L5O","created_at":"2026-05-18T12:28:06Z"},{"alias_kind":"pith_short_16","alias_value":"XOGM2ZHZ6L5OFC4U","created_at":"2026-05-18T12:28:06Z"},{"alias_kind":"pith_short_8","alias_value":"XOGM2ZHZ","created_at":"2026-05-18T12:28:06Z"}],"graph_snapshots":[{"event_id":"sha256:a2f1122d5c66237f7e79a9852e89799f485334f980653da8325908c5ed6a872e","target":"graph","created_at":"2026-05-18T03:22:05Z","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":"Recent advances in associative memory design through strutured pattern sets and graph-based inference algorithms have allowed the reliable learning and retrieval of an exponential number of patterns. Both these and classical associative memories, however, have assumed internally noiseless computational nodes. This paper considers the setting when internal computations are also noisy. Even if all components are noisy, the final error probability in recall can often be made exceedingly small, as we characterize. There is a threshold phenomenon. We also show how to optimize inference algorithm pa","authors_text":"Amin Karbasi, Amin Shokrollahi, Amir Hesam Salavati, Lav Varshney","cross_cats":["cs.IT","math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2013-01-26T16:20:46Z","title":"Neural Networks Built from Unreliable Components"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.6265","kind":"arxiv","version":4},"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":"sha256:9ac16da20893aced0334961ba8a94e7b1434381d7e2cb8b83a90ae08881f9aa1","target":"record","created_at":"2026-05-18T03:22:05Z","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":"62937bb57a94061e5e5854bd65df77a3c52572c69e36a36afabb4db52b2b38fd","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2013-01-26T16:20:46Z","title_canon_sha256":"4925444dcff528e62901f8043b100389caebd663589deb8fe42d6b04a25a18d7"},"schema_version":"1.0","source":{"id":"1301.6265","kind":"arxiv","version":4}},"canonical_sha256":"bb8ccd64f9f2fae28b947d38f94ab3e3cf04f66d37ff6253ee2c0302431ea94d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bb8ccd64f9f2fae28b947d38f94ab3e3cf04f66d37ff6253ee2c0302431ea94d","first_computed_at":"2026-05-18T03:22:05.601390Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:22:05.601390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nQuK4veQGEoyWQ8jgAmJbi+O0ybm21n69d+u1JD4NlbirnUgSUY1JKQnu4KPLRdPF0ybUafkCiBEgxuTzC0VAA==","signature_status":"signed_v1","signed_at":"2026-05-18T03:22:05.602215Z","signed_message":"canonical_sha256_bytes"},"source_id":"1301.6265","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9ac16da20893aced0334961ba8a94e7b1434381d7e2cb8b83a90ae08881f9aa1","sha256:a2f1122d5c66237f7e79a9852e89799f485334f980653da8325908c5ed6a872e"],"state_sha256":"ad38c7c134ee26a9eff360d413b328bae7b5c3475610685ac79e413a1e265324"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KIPZVKGdcRLqhv1pe5a2pJ+sk362Sie14bOn0e0UtfhBoXpvF9K7kJFTMdj3swnMNxKciHecgqEbx74d0t5LCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T19:56:01.617826Z","bundle_sha256":"d81089435d61db52370dc62f578f798a5e394b5ec3dd905868e075ae18f4818f"}}