{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:AHLSIF4YPBXSGQK4OHEP3NFQTG","short_pith_number":"pith:AHLSIF4Y","canonical_record":{"source":{"id":"1402.5876","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2014-02-24T16:19:51Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"285ff287d955314cbc353060ae6205d697a741663f631e23a37f03456d6db161","abstract_canon_sha256":"8b2f32180e5286ced7e63240019a42f79427dd7b0123bec9cbde0f4d9f7322e0"},"schema_version":"1.0"},"canonical_sha256":"01d7241798786f23415c71c8fdb4b099bf41908987bf33cd3b9122034ccd9c4f","source":{"kind":"arxiv","id":"1402.5876","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1402.5876","created_at":"2026-05-18T01:17:26Z"},{"alias_kind":"arxiv_version","alias_value":"1402.5876v4","created_at":"2026-05-18T01:17:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1402.5876","created_at":"2026-05-18T01:17:26Z"},{"alias_kind":"pith_short_12","alias_value":"AHLSIF4YPBXS","created_at":"2026-05-18T12:28:19Z"},{"alias_kind":"pith_short_16","alias_value":"AHLSIF4YPBXSGQK4","created_at":"2026-05-18T12:28:19Z"},{"alias_kind":"pith_short_8","alias_value":"AHLSIF4Y","created_at":"2026-05-18T12:28:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:AHLSIF4YPBXSGQK4OHEP3NFQTG","target":"record","payload":{"canonical_record":{"source":{"id":"1402.5876","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2014-02-24T16:19:51Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"285ff287d955314cbc353060ae6205d697a741663f631e23a37f03456d6db161","abstract_canon_sha256":"8b2f32180e5286ced7e63240019a42f79427dd7b0123bec9cbde0f4d9f7322e0"},"schema_version":"1.0"},"canonical_sha256":"01d7241798786f23415c71c8fdb4b099bf41908987bf33cd3b9122034ccd9c4f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:17:26.161100Z","signature_b64":"Ok1ZHR8IeWurHm9SvERLNpvAdYEv2ziAQFdSxVs42D9dwXpQKpJUvbily+uo5UA9xiKLj6eCu6UtOe/5leGMDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"01d7241798786f23415c71c8fdb4b099bf41908987bf33cd3b9122034ccd9c4f","last_reissued_at":"2026-05-18T01:17:26.160427Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:17:26.160427Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1402.5876","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:17:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VHFgd3Um+z4rzq2MbbuFBiWVkGNIiBY/3Rb+Gh9dqetvWZC/a5hSKatLOfthHMiZlMdW57ctkch360lsOcxnAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T01:19:57.049927Z"},"content_sha256":"efebf4425a07b64690c469051caf11aac030a5e191614cc238ac43927fb76cc4","schema_version":"1.0","event_id":"sha256:efebf4425a07b64690c469051caf11aac030a5e191614cc238ac43927fb76cc4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:AHLSIF4YPBXSGQK4OHEP3NFQTG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Manifold Gaussian Processes for Regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Carl Edward Rasmussen, Jan Peters, Marc Peter Deisenroth, Roberto Calandra","submitted_at":"2014-02-24T16:19:51Z","abstract_excerpt":"Off-the-shelf Gaussian Process (GP) covariance functions encode smoothness assumptions on the structure of the function to be modeled. To model complex and non-differentiable functions, these smoothness assumptions are often too restrictive. One way to alleviate this limitation is to find a different representation of the data by introducing a feature space. This feature space is often learned in an unsupervised way, which might lead to data representations that are not useful for the overall regression task. In this paper, we propose Manifold Gaussian Processes, a novel supervised method that"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1402.5876","kind":"arxiv","version":4},"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":"2026-05-18T01:17:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qXa/+tROma/fd0DWypiSs96LIoHzcXk7xmN7qPMBx6Fz5fUDpXlpiv2becvpV5y/k35dJ2eIIBhA4URkkUgQAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T01:19:57.050279Z"},"content_sha256":"2e5daa9a460f7f12bf5e1d64faadd5bf8d1c51b66c6f9e4fe50440bf8210c012","schema_version":"1.0","event_id":"sha256:2e5daa9a460f7f12bf5e1d64faadd5bf8d1c51b66c6f9e4fe50440bf8210c012"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AHLSIF4YPBXSGQK4OHEP3NFQTG/bundle.json","state_url":"https://pith.science/pith/AHLSIF4YPBXSGQK4OHEP3NFQTG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AHLSIF4YPBXSGQK4OHEP3NFQTG/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":"2026-06-02T01:19:57Z","links":{"resolver":"https://pith.science/pith/AHLSIF4YPBXSGQK4OHEP3NFQTG","bundle":"https://pith.science/pith/AHLSIF4YPBXSGQK4OHEP3NFQTG/bundle.json","state":"https://pith.science/pith/AHLSIF4YPBXSGQK4OHEP3NFQTG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AHLSIF4YPBXSGQK4OHEP3NFQTG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:AHLSIF4YPBXSGQK4OHEP3NFQTG","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":"8b2f32180e5286ced7e63240019a42f79427dd7b0123bec9cbde0f4d9f7322e0","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2014-02-24T16:19:51Z","title_canon_sha256":"285ff287d955314cbc353060ae6205d697a741663f631e23a37f03456d6db161"},"schema_version":"1.0","source":{"id":"1402.5876","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1402.5876","created_at":"2026-05-18T01:17:26Z"},{"alias_kind":"arxiv_version","alias_value":"1402.5876v4","created_at":"2026-05-18T01:17:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1402.5876","created_at":"2026-05-18T01:17:26Z"},{"alias_kind":"pith_short_12","alias_value":"AHLSIF4YPBXS","created_at":"2026-05-18T12:28:19Z"},{"alias_kind":"pith_short_16","alias_value":"AHLSIF4YPBXSGQK4","created_at":"2026-05-18T12:28:19Z"},{"alias_kind":"pith_short_8","alias_value":"AHLSIF4Y","created_at":"2026-05-18T12:28:19Z"}],"graph_snapshots":[{"event_id":"sha256:2e5daa9a460f7f12bf5e1d64faadd5bf8d1c51b66c6f9e4fe50440bf8210c012","target":"graph","created_at":"2026-05-18T01:17:26Z","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":"Off-the-shelf Gaussian Process (GP) covariance functions encode smoothness assumptions on the structure of the function to be modeled. To model complex and non-differentiable functions, these smoothness assumptions are often too restrictive. One way to alleviate this limitation is to find a different representation of the data by introducing a feature space. This feature space is often learned in an unsupervised way, which might lead to data representations that are not useful for the overall regression task. In this paper, we propose Manifold Gaussian Processes, a novel supervised method that","authors_text":"Carl Edward Rasmussen, Jan Peters, Marc Peter Deisenroth, Roberto Calandra","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2014-02-24T16:19:51Z","title":"Manifold Gaussian Processes for Regression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1402.5876","kind":"arxiv","version":4},"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:efebf4425a07b64690c469051caf11aac030a5e191614cc238ac43927fb76cc4","target":"record","created_at":"2026-05-18T01:17:26Z","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":"8b2f32180e5286ced7e63240019a42f79427dd7b0123bec9cbde0f4d9f7322e0","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2014-02-24T16:19:51Z","title_canon_sha256":"285ff287d955314cbc353060ae6205d697a741663f631e23a37f03456d6db161"},"schema_version":"1.0","source":{"id":"1402.5876","kind":"arxiv","version":4}},"canonical_sha256":"01d7241798786f23415c71c8fdb4b099bf41908987bf33cd3b9122034ccd9c4f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"01d7241798786f23415c71c8fdb4b099bf41908987bf33cd3b9122034ccd9c4f","first_computed_at":"2026-05-18T01:17:26.160427Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:17:26.160427Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ok1ZHR8IeWurHm9SvERLNpvAdYEv2ziAQFdSxVs42D9dwXpQKpJUvbily+uo5UA9xiKLj6eCu6UtOe/5leGMDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:17:26.161100Z","signed_message":"canonical_sha256_bytes"},"source_id":"1402.5876","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:efebf4425a07b64690c469051caf11aac030a5e191614cc238ac43927fb76cc4","sha256:2e5daa9a460f7f12bf5e1d64faadd5bf8d1c51b66c6f9e4fe50440bf8210c012"],"state_sha256":"b021e541f7e66a3e8a8e4085d8f364c675b785ddfa94e33c3d3edd7425c8aa56"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2zxpMIt4jdHdFMRG08u3jogYPUgkhIWZS8m+edQKNp2PMmwA6U9yybcmtKuEULbes27LMQvdwny0keRDgAwPAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T01:19:57.052245Z","bundle_sha256":"8326d7e967de5897f965c09eed82b3a3c280ec47da83f848331e8ff0b939f522"}}