{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:WDZ5PWLBMWPDHP3O3QS6AIHPDT","short_pith_number":"pith:WDZ5PWLB","canonical_record":{"source":{"id":"1810.02225","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.NE","submitted_at":"2018-09-14T18:47:34Z","cross_cats_sorted":["cs.ET","cs.LG","stat.ML"],"title_canon_sha256":"c137e49653c38c74469df9974ab32a283dde4d6dd54a9db09d849268e427ea5f","abstract_canon_sha256":"7db76eeedaa7db31175faaa710975ec3fb330300417b761f7092a61c804ae313"},"schema_version":"1.0"},"canonical_sha256":"b0f3d7d961659e33bf6edc25e020ef1ce947d76cd86f2cdad333800b5f752d8b","source":{"kind":"arxiv","id":"1810.02225","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.02225","created_at":"2026-05-18T00:04:05Z"},{"alias_kind":"arxiv_version","alias_value":"1810.02225v1","created_at":"2026-05-18T00:04:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.02225","created_at":"2026-05-18T00:04:05Z"},{"alias_kind":"pith_short_12","alias_value":"WDZ5PWLBMWPD","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"WDZ5PWLBMWPDHP3O","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"WDZ5PWLB","created_at":"2026-05-18T12:32:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:WDZ5PWLBMWPDHP3O3QS6AIHPDT","target":"record","payload":{"canonical_record":{"source":{"id":"1810.02225","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.NE","submitted_at":"2018-09-14T18:47:34Z","cross_cats_sorted":["cs.ET","cs.LG","stat.ML"],"title_canon_sha256":"c137e49653c38c74469df9974ab32a283dde4d6dd54a9db09d849268e427ea5f","abstract_canon_sha256":"7db76eeedaa7db31175faaa710975ec3fb330300417b761f7092a61c804ae313"},"schema_version":"1.0"},"canonical_sha256":"b0f3d7d961659e33bf6edc25e020ef1ce947d76cd86f2cdad333800b5f752d8b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:04:05.884652Z","signature_b64":"OhnVFJaj+hAs1GflB3dwnnZWxS6wlojdsisMiPbDJ4sN4NA5prxRf1/oEbwfpG3YMBWraBV/b0YZ/iVYaHRlDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b0f3d7d961659e33bf6edc25e020ef1ce947d76cd86f2cdad333800b5f752d8b","last_reissued_at":"2026-05-18T00:04:05.883945Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:04:05.883945Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.02225","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":"2026-05-18T00:04:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GkO9ZqXs9OOqYEJWzptT1D0M1sTKSkBtV9zD6WgRYRXeGLpthnOeks+WUnleMIifcXe3OioZJnPjSPauONDTCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T01:38:24.275086Z"},"content_sha256":"88e267cb3eb4cec38fe57a5e80eca201a81a04b4cf002d49d47043a9a7363507","schema_version":"1.0","event_id":"sha256:88e267cb3eb4cec38fe57a5e80eca201a81a04b4cf002d49d47043a9a7363507"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:WDZ5PWLBMWPDHP3O3QS6AIHPDT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Memristor-based Deep Convolution Neural Network: A Case Study","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.ET","cs.LG","stat.ML"],"primary_cat":"cs.NE","authors_text":"Fan Zhang, Miao Hu","submitted_at":"2018-09-14T18:47:34Z","abstract_excerpt":"In this paper, we firstly introduce a method to efficiently implement large-scale high-dimensional convolution with realistic memristor-based circuit components. An experiment verified simulator is adapted for accurate prediction of analog crossbar behavior. An improved conversion algorithm is developed to convert convolution kernels to memristor-based circuits, which minimizes the error with consideration of the data and kernel patterns in CNNs. With circuit simulation for all convolution layers in ResNet-20, we found that 8-bit ADC/DAC is necessary to preserve software level classification a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.02225","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":"2026-05-18T00:04:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dEg4UzWlZDG0wq1PKrXvGDgoLqEKWUp5WKCVUF6jUoXn2K3vfUkMyCJvMNN6ljYZB2A1m0VN1u15fnWIEV4CCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T01:38:24.275453Z"},"content_sha256":"e9f67e59d7b1b8857cda2608d2a8393eb10d55d36c5e04f70b36b2db264875b8","schema_version":"1.0","event_id":"sha256:e9f67e59d7b1b8857cda2608d2a8393eb10d55d36c5e04f70b36b2db264875b8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WDZ5PWLBMWPDHP3O3QS6AIHPDT/bundle.json","state_url":"https://pith.science/pith/WDZ5PWLBMWPDHP3O3QS6AIHPDT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WDZ5PWLBMWPDHP3O3QS6AIHPDT/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":"2026-06-20T01:38:24Z","links":{"resolver":"https://pith.science/pith/WDZ5PWLBMWPDHP3O3QS6AIHPDT","bundle":"https://pith.science/pith/WDZ5PWLBMWPDHP3O3QS6AIHPDT/bundle.json","state":"https://pith.science/pith/WDZ5PWLBMWPDHP3O3QS6AIHPDT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WDZ5PWLBMWPDHP3O3QS6AIHPDT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:WDZ5PWLBMWPDHP3O3QS6AIHPDT","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":"7db76eeedaa7db31175faaa710975ec3fb330300417b761f7092a61c804ae313","cross_cats_sorted":["cs.ET","cs.LG","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.NE","submitted_at":"2018-09-14T18:47:34Z","title_canon_sha256":"c137e49653c38c74469df9974ab32a283dde4d6dd54a9db09d849268e427ea5f"},"schema_version":"1.0","source":{"id":"1810.02225","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.02225","created_at":"2026-05-18T00:04:05Z"},{"alias_kind":"arxiv_version","alias_value":"1810.02225v1","created_at":"2026-05-18T00:04:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.02225","created_at":"2026-05-18T00:04:05Z"},{"alias_kind":"pith_short_12","alias_value":"WDZ5PWLBMWPD","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"WDZ5PWLBMWPDHP3O","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"WDZ5PWLB","created_at":"2026-05-18T12:32:59Z"}],"graph_snapshots":[{"event_id":"sha256:e9f67e59d7b1b8857cda2608d2a8393eb10d55d36c5e04f70b36b2db264875b8","target":"graph","created_at":"2026-05-18T00:04:05Z","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":"In this paper, we firstly introduce a method to efficiently implement large-scale high-dimensional convolution with realistic memristor-based circuit components. An experiment verified simulator is adapted for accurate prediction of analog crossbar behavior. An improved conversion algorithm is developed to convert convolution kernels to memristor-based circuits, which minimizes the error with consideration of the data and kernel patterns in CNNs. With circuit simulation for all convolution layers in ResNet-20, we found that 8-bit ADC/DAC is necessary to preserve software level classification a","authors_text":"Fan Zhang, Miao Hu","cross_cats":["cs.ET","cs.LG","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.NE","submitted_at":"2018-09-14T18:47:34Z","title":"Memristor-based Deep Convolution Neural Network: A Case Study"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.02225","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":"sha256:88e267cb3eb4cec38fe57a5e80eca201a81a04b4cf002d49d47043a9a7363507","target":"record","created_at":"2026-05-18T00:04:05Z","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":"7db76eeedaa7db31175faaa710975ec3fb330300417b761f7092a61c804ae313","cross_cats_sorted":["cs.ET","cs.LG","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.NE","submitted_at":"2018-09-14T18:47:34Z","title_canon_sha256":"c137e49653c38c74469df9974ab32a283dde4d6dd54a9db09d849268e427ea5f"},"schema_version":"1.0","source":{"id":"1810.02225","kind":"arxiv","version":1}},"canonical_sha256":"b0f3d7d961659e33bf6edc25e020ef1ce947d76cd86f2cdad333800b5f752d8b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b0f3d7d961659e33bf6edc25e020ef1ce947d76cd86f2cdad333800b5f752d8b","first_computed_at":"2026-05-18T00:04:05.883945Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:04:05.883945Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OhnVFJaj+hAs1GflB3dwnnZWxS6wlojdsisMiPbDJ4sN4NA5prxRf1/oEbwfpG3YMBWraBV/b0YZ/iVYaHRlDA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:04:05.884652Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.02225","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:88e267cb3eb4cec38fe57a5e80eca201a81a04b4cf002d49d47043a9a7363507","sha256:e9f67e59d7b1b8857cda2608d2a8393eb10d55d36c5e04f70b36b2db264875b8"],"state_sha256":"d57ed62a02bd590513d3714b1329e92462344a9a1b69f1095f95e3a65bc34e7f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ym8Ii4T7jKzb5q5M3pKuYhNJr5WMn456neUYcz+9gImXPcLsseK5emmWkxoPN3Mz/kNmNKEzCu0NtuDbVgTvAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-20T01:38:24.277352Z","bundle_sha256":"fe71edd54b3e64c814cdc8073bfa2df7b93fe998a67ddcf7aa533761078238de"}}