{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:CLZT4DHQF7B3LFM3ERGQQP6JQ4","short_pith_number":"pith:CLZT4DHQ","canonical_record":{"source":{"id":"1706.04032","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2017-06-13T12:58:41Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"f717986c82cc8277b310c710d305993270638a7abdb08d28daddd8bea00c61c7","abstract_canon_sha256":"ae11859dfcf7cc658704e6f02918876c7deb33e693aff93b0f782d8d60a41501"},"schema_version":"1.0"},"canonical_sha256":"12f33e0cf02fc3b5959b244d083fc98722d8d5c1cb44370e0fc7c499debad767","source":{"kind":"arxiv","id":"1706.04032","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.04032","created_at":"2026-05-17T23:39:37Z"},{"alias_kind":"arxiv_version","alias_value":"1706.04032v2","created_at":"2026-05-17T23:39:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.04032","created_at":"2026-05-17T23:39:37Z"},{"alias_kind":"pith_short_12","alias_value":"CLZT4DHQF7B3","created_at":"2026-05-18T12:31:10Z"},{"alias_kind":"pith_short_16","alias_value":"CLZT4DHQF7B3LFM3","created_at":"2026-05-18T12:31:10Z"},{"alias_kind":"pith_short_8","alias_value":"CLZT4DHQ","created_at":"2026-05-18T12:31:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:CLZT4DHQF7B3LFM3ERGQQP6JQ4","target":"record","payload":{"canonical_record":{"source":{"id":"1706.04032","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2017-06-13T12:58:41Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"f717986c82cc8277b310c710d305993270638a7abdb08d28daddd8bea00c61c7","abstract_canon_sha256":"ae11859dfcf7cc658704e6f02918876c7deb33e693aff93b0f782d8d60a41501"},"schema_version":"1.0"},"canonical_sha256":"12f33e0cf02fc3b5959b244d083fc98722d8d5c1cb44370e0fc7c499debad767","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:39:37.317094Z","signature_b64":"9WgCcUEmhKdgPBUfVmdUTKl5HJ4lhHWtjdXbXp1sRbcCHB4+pyNbpmFbTR78a7vqQiVs980YrvVyG02g4AEEBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"12f33e0cf02fc3b5959b244d083fc98722d8d5c1cb44370e0fc7c499debad767","last_reissued_at":"2026-05-17T23:39:37.316280Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:39:37.316280Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1706.04032","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":"2026-05-17T23:39:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4kfpAIBJ/TObDTEw51g4Hed465rVioebA3X4v8FGvm4sgi5dou7X/o81yzyFuBkXjHhaMjpb9qxy9j7n9k69DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T13:50:41.181782Z"},"content_sha256":"dad19972d35151af0f514af15846829bb8592f8018724f797f9ae6f6327b5eea","schema_version":"1.0","event_id":"sha256:dad19972d35151af0f514af15846829bb8592f8018724f797f9ae6f6327b5eea"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:CLZT4DHQF7B3LFM3ERGQQP6JQ4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Modified Hamiltonian Monte Carlo for Bayesian inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"stat.CO","authors_text":"Elena Akhmatskaya, Tijana Radivojevi\\'c","submitted_at":"2017-06-13T12:58:41Z","abstract_excerpt":"The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in computational statistics. We show that performance of HMC can be significantly improved by incorporating importance sampling and an irreversible part of the dynamics into a chain. This is achieved by replacing Hamiltonians in the Metropolis test with modified Hamiltonians, and a complete momentum update with a partial momentum refreshment. We call the resulting generalized HMC importance sampler---Mix & Match Hamiltonian Monte Carlo (MMHMC). The method is irreversible by construction and further benefit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.04032","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":"2026-05-17T23:39:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"k06J20e8kPtLOemYg2Dm4TtOE57ywfPOfKWcU7i9KRx1pOEjibTHzZY1j+q8STEm2sWEczYZp6Z8Dby/sMwjBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T13:50:41.182126Z"},"content_sha256":"46b2da378ba15771e47d6ac8e98f07af99c1690bf98c3e89cafb56804f9d12e7","schema_version":"1.0","event_id":"sha256:46b2da378ba15771e47d6ac8e98f07af99c1690bf98c3e89cafb56804f9d12e7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CLZT4DHQF7B3LFM3ERGQQP6JQ4/bundle.json","state_url":"https://pith.science/pith/CLZT4DHQF7B3LFM3ERGQQP6JQ4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CLZT4DHQF7B3LFM3ERGQQP6JQ4/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":"2026-06-22T13:50:41Z","links":{"resolver":"https://pith.science/pith/CLZT4DHQF7B3LFM3ERGQQP6JQ4","bundle":"https://pith.science/pith/CLZT4DHQF7B3LFM3ERGQQP6JQ4/bundle.json","state":"https://pith.science/pith/CLZT4DHQF7B3LFM3ERGQQP6JQ4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CLZT4DHQF7B3LFM3ERGQQP6JQ4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:CLZT4DHQF7B3LFM3ERGQQP6JQ4","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":"ae11859dfcf7cc658704e6f02918876c7deb33e693aff93b0f782d8d60a41501","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2017-06-13T12:58:41Z","title_canon_sha256":"f717986c82cc8277b310c710d305993270638a7abdb08d28daddd8bea00c61c7"},"schema_version":"1.0","source":{"id":"1706.04032","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.04032","created_at":"2026-05-17T23:39:37Z"},{"alias_kind":"arxiv_version","alias_value":"1706.04032v2","created_at":"2026-05-17T23:39:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.04032","created_at":"2026-05-17T23:39:37Z"},{"alias_kind":"pith_short_12","alias_value":"CLZT4DHQF7B3","created_at":"2026-05-18T12:31:10Z"},{"alias_kind":"pith_short_16","alias_value":"CLZT4DHQF7B3LFM3","created_at":"2026-05-18T12:31:10Z"},{"alias_kind":"pith_short_8","alias_value":"CLZT4DHQ","created_at":"2026-05-18T12:31:10Z"}],"graph_snapshots":[{"event_id":"sha256:46b2da378ba15771e47d6ac8e98f07af99c1690bf98c3e89cafb56804f9d12e7","target":"graph","created_at":"2026-05-17T23:39:37Z","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 Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in computational statistics. We show that performance of HMC can be significantly improved by incorporating importance sampling and an irreversible part of the dynamics into a chain. This is achieved by replacing Hamiltonians in the Metropolis test with modified Hamiltonians, and a complete momentum update with a partial momentum refreshment. We call the resulting generalized HMC importance sampler---Mix & Match Hamiltonian Monte Carlo (MMHMC). The method is irreversible by construction and further benefit","authors_text":"Elena Akhmatskaya, Tijana Radivojevi\\'c","cross_cats":["stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2017-06-13T12:58:41Z","title":"Modified Hamiltonian Monte Carlo for Bayesian inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.04032","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:dad19972d35151af0f514af15846829bb8592f8018724f797f9ae6f6327b5eea","target":"record","created_at":"2026-05-17T23:39:37Z","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":"ae11859dfcf7cc658704e6f02918876c7deb33e693aff93b0f782d8d60a41501","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2017-06-13T12:58:41Z","title_canon_sha256":"f717986c82cc8277b310c710d305993270638a7abdb08d28daddd8bea00c61c7"},"schema_version":"1.0","source":{"id":"1706.04032","kind":"arxiv","version":2}},"canonical_sha256":"12f33e0cf02fc3b5959b244d083fc98722d8d5c1cb44370e0fc7c499debad767","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"12f33e0cf02fc3b5959b244d083fc98722d8d5c1cb44370e0fc7c499debad767","first_computed_at":"2026-05-17T23:39:37.316280Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:39:37.316280Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9WgCcUEmhKdgPBUfVmdUTKl5HJ4lhHWtjdXbXp1sRbcCHB4+pyNbpmFbTR78a7vqQiVs980YrvVyG02g4AEEBQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:39:37.317094Z","signed_message":"canonical_sha256_bytes"},"source_id":"1706.04032","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dad19972d35151af0f514af15846829bb8592f8018724f797f9ae6f6327b5eea","sha256:46b2da378ba15771e47d6ac8e98f07af99c1690bf98c3e89cafb56804f9d12e7"],"state_sha256":"c8a8b89d1f09bc066d59bcf06e04a2051d5c21abc49160034d5bff92c305650c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BxQ1dtpHNpgxkXKsVsOreOxiP74jMlYbuDkJrli3bxBqsq8O8pRHSkS+Nppvv66XZJXbsPQpU0bp2pGCS81RBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-22T13:50:41.184044Z","bundle_sha256":"c2b1b246aa87ae20d24f6c76116d12b496c657f7eccd3f6bd19f4395d4260d2e"}}