{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:OPUQVKJT2NFQ4DY2SIUR5PUITI","short_pith_number":"pith:OPUQVKJT","canonical_record":{"source":{"id":"1305.3794","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2013-05-16T13:25:20Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"25e32408ed918f051160a659aff103a98de3cb42ad7a35329bddceee638dac67","abstract_canon_sha256":"42ced067cebe8240503fb853b21fd57c3c521f4c771079e856e4331d62a242f7"},"schema_version":"1.0"},"canonical_sha256":"73e90aa933d34b0e0f1a92291ebe889a0a41aa6cb84c9e2c27d41136c5546962","source":{"kind":"arxiv","id":"1305.3794","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1305.3794","created_at":"2026-05-18T03:25:13Z"},{"alias_kind":"arxiv_version","alias_value":"1305.3794v2","created_at":"2026-05-18T03:25:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1305.3794","created_at":"2026-05-18T03:25:13Z"},{"alias_kind":"pith_short_12","alias_value":"OPUQVKJT2NFQ","created_at":"2026-05-18T12:27:54Z"},{"alias_kind":"pith_short_16","alias_value":"OPUQVKJT2NFQ4DY2","created_at":"2026-05-18T12:27:54Z"},{"alias_kind":"pith_short_8","alias_value":"OPUQVKJT","created_at":"2026-05-18T12:27:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:OPUQVKJT2NFQ4DY2SIUR5PUITI","target":"record","payload":{"canonical_record":{"source":{"id":"1305.3794","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2013-05-16T13:25:20Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"25e32408ed918f051160a659aff103a98de3cb42ad7a35329bddceee638dac67","abstract_canon_sha256":"42ced067cebe8240503fb853b21fd57c3c521f4c771079e856e4331d62a242f7"},"schema_version":"1.0"},"canonical_sha256":"73e90aa933d34b0e0f1a92291ebe889a0a41aa6cb84c9e2c27d41136c5546962","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:25:13.941091Z","signature_b64":"KuqpbNz3S2nUmakKIXMCoQoYU8Tp0f+CdFO0SxNs046TmmuoC60gJfFg3rcmnXx7iW5T6JqUM0hGNWYUNyQeBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"73e90aa933d34b0e0f1a92291ebe889a0a41aa6cb84c9e2c27d41136c5546962","last_reissued_at":"2026-05-18T03:25:13.940485Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:25:13.940485Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1305.3794","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":"2026-05-18T03:25:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8zyU8ntBcaBS6tHDaKTFqAe5IwE4Z7vMl2m9+0cLS4RuoB/NeuR+P88hH0P9nE/lH8Bv2ZHphW9lzV49YYOnDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T15:47:06.953309Z"},"content_sha256":"e7ede8dfb827b7557bc5ee5f36fb1bc257ac9ff5e4c558df022e62db643edd5f","schema_version":"1.0","event_id":"sha256:e7ede8dfb827b7557bc5ee5f36fb1bc257ac9ff5e4c558df022e62db643edd5f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:OPUQVKJT2NFQ4DY2SIUR5PUITI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evolution of Covariance Functions for Gaussian Process Regression using Genetic Programming","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.NE","authors_text":"Gabriel Kronberger, Michael Kommenda","submitted_at":"2013-05-16T13:25:20Z","abstract_excerpt":"In this contribution we describe an approach to evolve composite covariance functions for Gaussian processes using genetic programming. A critical aspect of Gaussian processes and similar kernel-based models such as SVM is, that the covariance function should be adapted to the modeled data. Frequently, the squared exponential covariance function is used as a default. However, this can lead to a misspecified model, which does not fit the data well. In the proposed approach we use a grammar for the composition of covariance functions and genetic programming to search over the space of sentences "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1305.3794","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":"2026-05-18T03:25:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Vcnm1ZO1ExSBPwHtti21IbBdIhlyogleu/g9Pr08ybVbSY+0WPRMAVsZnTk9EERCL2KzQxcoGl4tf6tRH+bzAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T15:47:06.953691Z"},"content_sha256":"884b5f502b5017f072db6d3e34df66e309a21ec4655de88198ca07d22cd095d7","schema_version":"1.0","event_id":"sha256:884b5f502b5017f072db6d3e34df66e309a21ec4655de88198ca07d22cd095d7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OPUQVKJT2NFQ4DY2SIUR5PUITI/bundle.json","state_url":"https://pith.science/pith/OPUQVKJT2NFQ4DY2SIUR5PUITI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OPUQVKJT2NFQ4DY2SIUR5PUITI/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":"2026-05-30T15:47:06Z","links":{"resolver":"https://pith.science/pith/OPUQVKJT2NFQ4DY2SIUR5PUITI","bundle":"https://pith.science/pith/OPUQVKJT2NFQ4DY2SIUR5PUITI/bundle.json","state":"https://pith.science/pith/OPUQVKJT2NFQ4DY2SIUR5PUITI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OPUQVKJT2NFQ4DY2SIUR5PUITI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:OPUQVKJT2NFQ4DY2SIUR5PUITI","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":"42ced067cebe8240503fb853b21fd57c3c521f4c771079e856e4331d62a242f7","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2013-05-16T13:25:20Z","title_canon_sha256":"25e32408ed918f051160a659aff103a98de3cb42ad7a35329bddceee638dac67"},"schema_version":"1.0","source":{"id":"1305.3794","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1305.3794","created_at":"2026-05-18T03:25:13Z"},{"alias_kind":"arxiv_version","alias_value":"1305.3794v2","created_at":"2026-05-18T03:25:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1305.3794","created_at":"2026-05-18T03:25:13Z"},{"alias_kind":"pith_short_12","alias_value":"OPUQVKJT2NFQ","created_at":"2026-05-18T12:27:54Z"},{"alias_kind":"pith_short_16","alias_value":"OPUQVKJT2NFQ4DY2","created_at":"2026-05-18T12:27:54Z"},{"alias_kind":"pith_short_8","alias_value":"OPUQVKJT","created_at":"2026-05-18T12:27:54Z"}],"graph_snapshots":[{"event_id":"sha256:884b5f502b5017f072db6d3e34df66e309a21ec4655de88198ca07d22cd095d7","target":"graph","created_at":"2026-05-18T03:25:13Z","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 contribution we describe an approach to evolve composite covariance functions for Gaussian processes using genetic programming. A critical aspect of Gaussian processes and similar kernel-based models such as SVM is, that the covariance function should be adapted to the modeled data. Frequently, the squared exponential covariance function is used as a default. However, this can lead to a misspecified model, which does not fit the data well. In the proposed approach we use a grammar for the composition of covariance functions and genetic programming to search over the space of sentences ","authors_text":"Gabriel Kronberger, Michael Kommenda","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2013-05-16T13:25:20Z","title":"Evolution of Covariance Functions for Gaussian Process Regression using Genetic Programming"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1305.3794","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:e7ede8dfb827b7557bc5ee5f36fb1bc257ac9ff5e4c558df022e62db643edd5f","target":"record","created_at":"2026-05-18T03:25:13Z","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":"42ced067cebe8240503fb853b21fd57c3c521f4c771079e856e4331d62a242f7","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2013-05-16T13:25:20Z","title_canon_sha256":"25e32408ed918f051160a659aff103a98de3cb42ad7a35329bddceee638dac67"},"schema_version":"1.0","source":{"id":"1305.3794","kind":"arxiv","version":2}},"canonical_sha256":"73e90aa933d34b0e0f1a92291ebe889a0a41aa6cb84c9e2c27d41136c5546962","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"73e90aa933d34b0e0f1a92291ebe889a0a41aa6cb84c9e2c27d41136c5546962","first_computed_at":"2026-05-18T03:25:13.940485Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:25:13.940485Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KuqpbNz3S2nUmakKIXMCoQoYU8Tp0f+CdFO0SxNs046TmmuoC60gJfFg3rcmnXx7iW5T6JqUM0hGNWYUNyQeBw==","signature_status":"signed_v1","signed_at":"2026-05-18T03:25:13.941091Z","signed_message":"canonical_sha256_bytes"},"source_id":"1305.3794","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e7ede8dfb827b7557bc5ee5f36fb1bc257ac9ff5e4c558df022e62db643edd5f","sha256:884b5f502b5017f072db6d3e34df66e309a21ec4655de88198ca07d22cd095d7"],"state_sha256":"96e6614313a67c187843cb7bc1b651cfba1d4288feb2ae1cddd4f31652106172"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5YxQPLsp4//wAnohjKEyTrbqsjLyWBepBf+hzpEujgQts5Tn0SqUORB5W+BRtc5o5JUglwMJpaFNxpGK42XGDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T15:47:06.955748Z","bundle_sha256":"106d6fae949ff820c92a8f741479cb160352a21246a1e2eae7b468b3a5a3bc0f"}}