{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:QXZOJYNG4MCGQSDIUQB6HLER6R","short_pith_number":"pith:QXZOJYNG","canonical_record":{"source":{"id":"1811.12335","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-11-29T17:37:22Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"d36257a6aa2a0386bff29a0f93be6e4d6e1428dd856b94e6245a204777992bb0","abstract_canon_sha256":"6e0348e58777771b08a7fa2e46274ecf3160eb881119348601a1bc350b33c8d2"},"schema_version":"1.0"},"canonical_sha256":"85f2e4e1a6e304684868a403e3ac91f45a655a16da2561f9bce15a942cc903b4","source":{"kind":"arxiv","id":"1811.12335","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.12335","created_at":"2026-05-17T23:59:33Z"},{"alias_kind":"arxiv_version","alias_value":"1811.12335v1","created_at":"2026-05-17T23:59:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.12335","created_at":"2026-05-17T23:59:33Z"},{"alias_kind":"pith_short_12","alias_value":"QXZOJYNG4MCG","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"QXZOJYNG4MCGQSDI","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"QXZOJYNG","created_at":"2026-05-18T12:32:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:QXZOJYNG4MCGQSDIUQB6HLER6R","target":"record","payload":{"canonical_record":{"source":{"id":"1811.12335","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-11-29T17:37:22Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"d36257a6aa2a0386bff29a0f93be6e4d6e1428dd856b94e6245a204777992bb0","abstract_canon_sha256":"6e0348e58777771b08a7fa2e46274ecf3160eb881119348601a1bc350b33c8d2"},"schema_version":"1.0"},"canonical_sha256":"85f2e4e1a6e304684868a403e3ac91f45a655a16da2561f9bce15a942cc903b4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:59:33.752543Z","signature_b64":"PNPhJ6RwLD06EYd0zDXGgrqPfH+/apQT60Gx+GWklSQKBYCTzPXXZ/reV842StWxlqwBUDHR838xGngAmykEDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"85f2e4e1a6e304684868a403e3ac91f45a655a16da2561f9bce15a942cc903b4","last_reissued_at":"2026-05-17T23:59:33.751858Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:59:33.751858Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.12335","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":"2026-05-17T23:59:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DXifb1pKc60HUlgNr6b6Coh5dRahJgaoRvbNhm24c0H1WPmkjhvtTmrzrM936/YjmlBKzigywLMoQoKW3Z54Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T12:41:16.722406Z"},"content_sha256":"c07997be1c44e51fb130b6abef3661f7f2821b0dc6f15eb9d3f1f8f8342a85d9","schema_version":"1.0","event_id":"sha256:c07997be1c44e51fb130b6abef3661f7f2821b0dc6f15eb9d3f1f8f8342a85d9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:QXZOJYNG4MCGQSDIUQB6HLER6R","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Artur Bekasov, Iain Murray","submitted_at":"2018-11-29T17:37:22Z","abstract_excerpt":"Modern deep neural network models suffer from adversarial examples, i.e. confidently misclassified points in the input space. It has been shown that Bayesian neural networks are a promising approach for detecting adversarial points, but careful analysis is problematic due to the complexity of these models. Recently Gilmer et al. (2018) introduced adversarial spheres, a toy set-up that simplifies both practical and theoretical analysis of the problem. In this work, we use the adversarial sphere set-up to understand the properties of approximate Bayesian inference methods for a linear model in a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.12335","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":"2026-05-17T23:59:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qMPQvb5wshjGz1TCRnCpxJXIg6qLL9yaJQNSXdpOAzXuk5iWvcYW28IhJmaqOiqzU/SRB1rrak4uUzPWLHclDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T12:41:16.723096Z"},"content_sha256":"84539a17f70c9b2a64a8dedb6df4ebc19252eb9bd5382985352435aebaaf1272","schema_version":"1.0","event_id":"sha256:84539a17f70c9b2a64a8dedb6df4ebc19252eb9bd5382985352435aebaaf1272"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QXZOJYNG4MCGQSDIUQB6HLER6R/bundle.json","state_url":"https://pith.science/pith/QXZOJYNG4MCGQSDIUQB6HLER6R/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QXZOJYNG4MCGQSDIUQB6HLER6R/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":"2026-06-10T12:41:16Z","links":{"resolver":"https://pith.science/pith/QXZOJYNG4MCGQSDIUQB6HLER6R","bundle":"https://pith.science/pith/QXZOJYNG4MCGQSDIUQB6HLER6R/bundle.json","state":"https://pith.science/pith/QXZOJYNG4MCGQSDIUQB6HLER6R/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QXZOJYNG4MCGQSDIUQB6HLER6R/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:QXZOJYNG4MCGQSDIUQB6HLER6R","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":"6e0348e58777771b08a7fa2e46274ecf3160eb881119348601a1bc350b33c8d2","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-11-29T17:37:22Z","title_canon_sha256":"d36257a6aa2a0386bff29a0f93be6e4d6e1428dd856b94e6245a204777992bb0"},"schema_version":"1.0","source":{"id":"1811.12335","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.12335","created_at":"2026-05-17T23:59:33Z"},{"alias_kind":"arxiv_version","alias_value":"1811.12335v1","created_at":"2026-05-17T23:59:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.12335","created_at":"2026-05-17T23:59:33Z"},{"alias_kind":"pith_short_12","alias_value":"QXZOJYNG4MCG","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"QXZOJYNG4MCGQSDI","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"QXZOJYNG","created_at":"2026-05-18T12:32:50Z"}],"graph_snapshots":[{"event_id":"sha256:84539a17f70c9b2a64a8dedb6df4ebc19252eb9bd5382985352435aebaaf1272","target":"graph","created_at":"2026-05-17T23:59:33Z","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":"Modern deep neural network models suffer from adversarial examples, i.e. confidently misclassified points in the input space. It has been shown that Bayesian neural networks are a promising approach for detecting adversarial points, but careful analysis is problematic due to the complexity of these models. Recently Gilmer et al. (2018) introduced adversarial spheres, a toy set-up that simplifies both practical and theoretical analysis of the problem. In this work, we use the adversarial sphere set-up to understand the properties of approximate Bayesian inference methods for a linear model in a","authors_text":"Artur Bekasov, Iain Murray","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-11-29T17:37:22Z","title":"Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.12335","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:c07997be1c44e51fb130b6abef3661f7f2821b0dc6f15eb9d3f1f8f8342a85d9","target":"record","created_at":"2026-05-17T23:59:33Z","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":"6e0348e58777771b08a7fa2e46274ecf3160eb881119348601a1bc350b33c8d2","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-11-29T17:37:22Z","title_canon_sha256":"d36257a6aa2a0386bff29a0f93be6e4d6e1428dd856b94e6245a204777992bb0"},"schema_version":"1.0","source":{"id":"1811.12335","kind":"arxiv","version":1}},"canonical_sha256":"85f2e4e1a6e304684868a403e3ac91f45a655a16da2561f9bce15a942cc903b4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"85f2e4e1a6e304684868a403e3ac91f45a655a16da2561f9bce15a942cc903b4","first_computed_at":"2026-05-17T23:59:33.751858Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:59:33.751858Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PNPhJ6RwLD06EYd0zDXGgrqPfH+/apQT60Gx+GWklSQKBYCTzPXXZ/reV842StWxlqwBUDHR838xGngAmykEDw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:59:33.752543Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.12335","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c07997be1c44e51fb130b6abef3661f7f2821b0dc6f15eb9d3f1f8f8342a85d9","sha256:84539a17f70c9b2a64a8dedb6df4ebc19252eb9bd5382985352435aebaaf1272"],"state_sha256":"bc995c7399872a507b36756873f45a8b5e9e2584e3ced52d8b1db2f8f82c0c25"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m4NIcpQ6TOxPfcnZTH1qQ9a6gBh/9UvfKuz01exIh1iOQ/1NQM3yBEpspnsQSSKG9ScqHM8rFcjZr7OYsgTuCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T12:41:16.726995Z","bundle_sha256":"764469606b9cb0abeef910a50d21db18b21581d82606070f0e56223b6b6d505a"}}