{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:X6O7BAVZM4WRGDLSV3QBJLC4VW","short_pith_number":"pith:X6O7BAVZ","canonical_record":{"source":{"id":"1412.8659","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-12-30T15:32:18Z","cross_cats_sorted":[],"title_canon_sha256":"38a0117593649e094b2efff0533dbf811926d6a01a6ae2f1f29add5b445d3265","abstract_canon_sha256":"d39e9b9eadfb21106ee94e5bdc887341258c95ee9278b2e8ff76f1b6dd4af297"},"schema_version":"1.0"},"canonical_sha256":"bf9df082b9672d130d72aee014ac5cad9130111fa85ba2ade1b3b7b7d711bcce","source":{"kind":"arxiv","id":"1412.8659","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1412.8659","created_at":"2026-05-18T01:59:57Z"},{"alias_kind":"arxiv_version","alias_value":"1412.8659v2","created_at":"2026-05-18T01:59:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1412.8659","created_at":"2026-05-18T01:59:57Z"},{"alias_kind":"pith_short_12","alias_value":"X6O7BAVZM4WR","created_at":"2026-05-18T12:28:57Z"},{"alias_kind":"pith_short_16","alias_value":"X6O7BAVZM4WRGDLS","created_at":"2026-05-18T12:28:57Z"},{"alias_kind":"pith_short_8","alias_value":"X6O7BAVZ","created_at":"2026-05-18T12:28:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:X6O7BAVZM4WRGDLSV3QBJLC4VW","target":"record","payload":{"canonical_record":{"source":{"id":"1412.8659","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-12-30T15:32:18Z","cross_cats_sorted":[],"title_canon_sha256":"38a0117593649e094b2efff0533dbf811926d6a01a6ae2f1f29add5b445d3265","abstract_canon_sha256":"d39e9b9eadfb21106ee94e5bdc887341258c95ee9278b2e8ff76f1b6dd4af297"},"schema_version":"1.0"},"canonical_sha256":"bf9df082b9672d130d72aee014ac5cad9130111fa85ba2ade1b3b7b7d711bcce","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:59:57.935036Z","signature_b64":"9M8PmttHrmFEdIzD14Kt2MwegcNSYv44XTZV0diy6E6pUHTxoU/E614onxqmtPSO4yQhpM40qUGv2Ivdt30uAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bf9df082b9672d130d72aee014ac5cad9130111fa85ba2ade1b3b7b7d711bcce","last_reissued_at":"2026-05-18T01:59:57.934328Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:59:57.934328Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1412.8659","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:59:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Qj0n3SBxD73FpwpvfZQ4O7yez8DV8smVHR0L8Xfa3IiUtWk2NEXzNpARkDuc2rvjTwItotZpqfeSIE0PVfv0DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T22:42:12.587170Z"},"content_sha256":"61a019eb05c72dedb56436da8d107922914659d53b14b7582a4bf347a1bad4d9","schema_version":"1.0","event_id":"sha256:61a019eb05c72dedb56436da8d107922914659d53b14b7582a4bf347a1bad4d9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:X6O7BAVZM4WRGDLSV3QBJLC4VW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Roto-Translation Scattering for Object Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Edouard Oyallon, St\\'ephane Mallat","submitted_at":"2014-12-30T15:32:18Z","abstract_excerpt":"Dictionary learning algorithms or supervised deep convolution networks have considerably improved the efficiency of predefined feature representations such as SIFT. We introduce a deep scattering convolution network, with predefined wavelet filters over spatial and angular variables. This representation brings an important improvement to results previously obtained with predefined features over object image databases such as Caltech and CIFAR. The resulting accuracy is comparable to results obtained with unsupervised deep learning and dictionary based representations. This shows that refining "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1412.8659","kind":"arxiv","version":2},"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":"2026-05-18T01:59:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Fp1TLiCZhfJ7PtuzI1CWVhaGRAm3U6A7ggQTq57eKJkbQHe9xf8jHPxzR5VMg3Nj3STcA/kH+190TFAzw662AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T22:42:12.587772Z"},"content_sha256":"e50cba3e0235d95ab7e3eab9e904f32c89f27c860191448433103cef2ae46790","schema_version":"1.0","event_id":"sha256:e50cba3e0235d95ab7e3eab9e904f32c89f27c860191448433103cef2ae46790"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X6O7BAVZM4WRGDLSV3QBJLC4VW/bundle.json","state_url":"https://pith.science/pith/X6O7BAVZM4WRGDLSV3QBJLC4VW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X6O7BAVZM4WRGDLSV3QBJLC4VW/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":"2026-06-22T22:42:12Z","links":{"resolver":"https://pith.science/pith/X6O7BAVZM4WRGDLSV3QBJLC4VW","bundle":"https://pith.science/pith/X6O7BAVZM4WRGDLSV3QBJLC4VW/bundle.json","state":"https://pith.science/pith/X6O7BAVZM4WRGDLSV3QBJLC4VW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X6O7BAVZM4WRGDLSV3QBJLC4VW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:X6O7BAVZM4WRGDLSV3QBJLC4VW","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":"d39e9b9eadfb21106ee94e5bdc887341258c95ee9278b2e8ff76f1b6dd4af297","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-12-30T15:32:18Z","title_canon_sha256":"38a0117593649e094b2efff0533dbf811926d6a01a6ae2f1f29add5b445d3265"},"schema_version":"1.0","source":{"id":"1412.8659","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1412.8659","created_at":"2026-05-18T01:59:57Z"},{"alias_kind":"arxiv_version","alias_value":"1412.8659v2","created_at":"2026-05-18T01:59:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1412.8659","created_at":"2026-05-18T01:59:57Z"},{"alias_kind":"pith_short_12","alias_value":"X6O7BAVZM4WR","created_at":"2026-05-18T12:28:57Z"},{"alias_kind":"pith_short_16","alias_value":"X6O7BAVZM4WRGDLS","created_at":"2026-05-18T12:28:57Z"},{"alias_kind":"pith_short_8","alias_value":"X6O7BAVZ","created_at":"2026-05-18T12:28:57Z"}],"graph_snapshots":[{"event_id":"sha256:e50cba3e0235d95ab7e3eab9e904f32c89f27c860191448433103cef2ae46790","target":"graph","created_at":"2026-05-18T01:59:57Z","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":"Dictionary learning algorithms or supervised deep convolution networks have considerably improved the efficiency of predefined feature representations such as SIFT. We introduce a deep scattering convolution network, with predefined wavelet filters over spatial and angular variables. This representation brings an important improvement to results previously obtained with predefined features over object image databases such as Caltech and CIFAR. The resulting accuracy is comparable to results obtained with unsupervised deep learning and dictionary based representations. This shows that refining ","authors_text":"Edouard Oyallon, St\\'ephane Mallat","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-12-30T15:32:18Z","title":"Deep Roto-Translation Scattering for Object Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1412.8659","kind":"arxiv","version":2},"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":"sha256:61a019eb05c72dedb56436da8d107922914659d53b14b7582a4bf347a1bad4d9","target":"record","created_at":"2026-05-18T01:59:57Z","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":"d39e9b9eadfb21106ee94e5bdc887341258c95ee9278b2e8ff76f1b6dd4af297","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-12-30T15:32:18Z","title_canon_sha256":"38a0117593649e094b2efff0533dbf811926d6a01a6ae2f1f29add5b445d3265"},"schema_version":"1.0","source":{"id":"1412.8659","kind":"arxiv","version":2}},"canonical_sha256":"bf9df082b9672d130d72aee014ac5cad9130111fa85ba2ade1b3b7b7d711bcce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bf9df082b9672d130d72aee014ac5cad9130111fa85ba2ade1b3b7b7d711bcce","first_computed_at":"2026-05-18T01:59:57.934328Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:59:57.934328Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9M8PmttHrmFEdIzD14Kt2MwegcNSYv44XTZV0diy6E6pUHTxoU/E614onxqmtPSO4yQhpM40qUGv2Ivdt30uAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:59:57.935036Z","signed_message":"canonical_sha256_bytes"},"source_id":"1412.8659","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:61a019eb05c72dedb56436da8d107922914659d53b14b7582a4bf347a1bad4d9","sha256:e50cba3e0235d95ab7e3eab9e904f32c89f27c860191448433103cef2ae46790"],"state_sha256":"47345748b6b346cc0b09850b4a7d46fa3ab2ff8748139e88fe2be5663fec6187"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pVmqQMF0cpZwga0dOaYpk34DQGQgqvDO/z0aJb9w/QYx0ftQqOYPCx5F5OfWJibJLULID79HUJVyYCxPMFj8Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-22T22:42:12.590444Z","bundle_sha256":"3bc6d79e6624ca55a4c2b1ba0652d3cfff108efbf2736543dcd1fdf2d4f6183d"}}