{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:PBAQIDGBF73TPQLUK536KYVQ3H","short_pith_number":"pith:PBAQIDGB","canonical_record":{"source":{"id":"1805.08355","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-22T02:12:33Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6c56a18cfcf645250004dbaee4930d4028b3dd6bf3e5721bf74b7267f15c64dd","abstract_canon_sha256":"ca8490ad48aabd0f5254fffa388d5e950973140010e1f4587b7b9233469365ce"},"schema_version":"1.0"},"canonical_sha256":"7841040cc12ff737c1745777e562b0d9c48011f37dd16328940a43100f9fe87d","source":{"kind":"arxiv","id":"1805.08355","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.08355","created_at":"2026-05-18T00:15:26Z"},{"alias_kind":"arxiv_version","alias_value":"1805.08355v1","created_at":"2026-05-18T00:15:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.08355","created_at":"2026-05-18T00:15:26Z"},{"alias_kind":"pith_short_12","alias_value":"PBAQIDGBF73T","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"PBAQIDGBF73TPQLU","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"PBAQIDGB","created_at":"2026-05-18T12:32:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:PBAQIDGBF73TPQLUK536KYVQ3H","target":"record","payload":{"canonical_record":{"source":{"id":"1805.08355","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-22T02:12:33Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6c56a18cfcf645250004dbaee4930d4028b3dd6bf3e5721bf74b7267f15c64dd","abstract_canon_sha256":"ca8490ad48aabd0f5254fffa388d5e950973140010e1f4587b7b9233469365ce"},"schema_version":"1.0"},"canonical_sha256":"7841040cc12ff737c1745777e562b0d9c48011f37dd16328940a43100f9fe87d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:15:26.791889Z","signature_b64":"7uS9RjXsdetKclC6QvSTX3gz+HRHJExhRFRP2qkqYbno5a+01x4VUUkELoQjESnXZlym/OhJXqPt44vMOFa4Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7841040cc12ff737c1745777e562b0d9c48011f37dd16328940a43100f9fe87d","last_reissued_at":"2026-05-18T00:15:26.791197Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:15:26.791197Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.08355","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":"2026-05-18T00:15:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gUudsfrVkCVu0mFWyMsycJf8ttBTN4nmerG4/rUI5+y2gat7533Wc03yI6wPCsjYMpbw3yQdV6tF4ZOwEgkiDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T07:30:38.099521Z"},"content_sha256":"9540e752789a805048e9cc37e87624ef103a0933294ba8b2e9262182f1158e33","schema_version":"1.0","event_id":"sha256:9540e752789a805048e9cc37e87624ef103a0933294ba8b2e9262182f1158e33"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:PBAQIDGBF73TPQLUK536KYVQ3H","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Opening the black box of deep learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Dian Lei, Jianfei Zhao, Xiaoxiao Chen","submitted_at":"2018-05-22T02:12:33Z","abstract_excerpt":"The great success of deep learning shows that its technology contains profound truth, and understanding its internal mechanism not only has important implications for the development of its technology and effective application in various fields, but also provides meaningful insights into the understanding of human brain mechanism. At present, most of the theoretical research on deep learning is based on mathematics. This dissertation proposes that the neural network of deep learning is a physical system, examines deep learning from three different perspectives: microscopic, macroscopic, and ph"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.08355","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":"2026-05-18T00:15:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lhYhTHnG2NHJqzVkErhBR/5IprfnR9hDzgV2smnViVKyredu9Ks4/nS8e7VQGn0liQ7VHHJRxa1FCNwMciMpAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T07:30:38.099861Z"},"content_sha256":"88ba65805d923012ffffac04fe4d0bb42a6410736c84948ba12dc7441ee49cae","schema_version":"1.0","event_id":"sha256:88ba65805d923012ffffac04fe4d0bb42a6410736c84948ba12dc7441ee49cae"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PBAQIDGBF73TPQLUK536KYVQ3H/bundle.json","state_url":"https://pith.science/pith/PBAQIDGBF73TPQLUK536KYVQ3H/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PBAQIDGBF73TPQLUK536KYVQ3H/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":"2026-07-06T07:30:38Z","links":{"resolver":"https://pith.science/pith/PBAQIDGBF73TPQLUK536KYVQ3H","bundle":"https://pith.science/pith/PBAQIDGBF73TPQLUK536KYVQ3H/bundle.json","state":"https://pith.science/pith/PBAQIDGBF73TPQLUK536KYVQ3H/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PBAQIDGBF73TPQLUK536KYVQ3H/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:PBAQIDGBF73TPQLUK536KYVQ3H","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":"ca8490ad48aabd0f5254fffa388d5e950973140010e1f4587b7b9233469365ce","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-22T02:12:33Z","title_canon_sha256":"6c56a18cfcf645250004dbaee4930d4028b3dd6bf3e5721bf74b7267f15c64dd"},"schema_version":"1.0","source":{"id":"1805.08355","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.08355","created_at":"2026-05-18T00:15:26Z"},{"alias_kind":"arxiv_version","alias_value":"1805.08355v1","created_at":"2026-05-18T00:15:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.08355","created_at":"2026-05-18T00:15:26Z"},{"alias_kind":"pith_short_12","alias_value":"PBAQIDGBF73T","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"PBAQIDGBF73TPQLU","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"PBAQIDGB","created_at":"2026-05-18T12:32:43Z"}],"graph_snapshots":[{"event_id":"sha256:88ba65805d923012ffffac04fe4d0bb42a6410736c84948ba12dc7441ee49cae","target":"graph","created_at":"2026-05-18T00:15:26Z","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 great success of deep learning shows that its technology contains profound truth, and understanding its internal mechanism not only has important implications for the development of its technology and effective application in various fields, but also provides meaningful insights into the understanding of human brain mechanism. At present, most of the theoretical research on deep learning is based on mathematics. This dissertation proposes that the neural network of deep learning is a physical system, examines deep learning from three different perspectives: microscopic, macroscopic, and ph","authors_text":"Dian Lei, Jianfei Zhao, Xiaoxiao Chen","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-22T02:12:33Z","title":"Opening the black box of deep learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.08355","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":"sha256:9540e752789a805048e9cc37e87624ef103a0933294ba8b2e9262182f1158e33","target":"record","created_at":"2026-05-18T00:15:26Z","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":"ca8490ad48aabd0f5254fffa388d5e950973140010e1f4587b7b9233469365ce","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-22T02:12:33Z","title_canon_sha256":"6c56a18cfcf645250004dbaee4930d4028b3dd6bf3e5721bf74b7267f15c64dd"},"schema_version":"1.0","source":{"id":"1805.08355","kind":"arxiv","version":1}},"canonical_sha256":"7841040cc12ff737c1745777e562b0d9c48011f37dd16328940a43100f9fe87d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7841040cc12ff737c1745777e562b0d9c48011f37dd16328940a43100f9fe87d","first_computed_at":"2026-05-18T00:15:26.791197Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:15:26.791197Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7uS9RjXsdetKclC6QvSTX3gz+HRHJExhRFRP2qkqYbno5a+01x4VUUkELoQjESnXZlym/OhJXqPt44vMOFa4Bw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:15:26.791889Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.08355","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9540e752789a805048e9cc37e87624ef103a0933294ba8b2e9262182f1158e33","sha256:88ba65805d923012ffffac04fe4d0bb42a6410736c84948ba12dc7441ee49cae"],"state_sha256":"d37f337a965371cbf84b3b3e790a656159e64e5bf8d2045b9e8512b5d5972d27"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OyUYpzyNuLGLmP0gio/P45rcMFLzUcm566oPSe2bcOxqo8iBN4GA+P7TDBVdnrjdcLfu46Ed7RBeyr2LLzWwAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T07:30:38.101722Z","bundle_sha256":"7d1abe77cf8550643684a330367ab786f03e7f8998dd0d5ff6fe10026427b38e"}}