{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:H74CA3JCPJRJ7YBJQHAG2FCHAP","short_pith_number":"pith:H74CA3JC","canonical_record":{"source":{"id":"1612.00767","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-12-02T17:43:33Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"fe4e84fd7aa08533eb6d89071c41f55e5ef664a761bb7e487ec42a1ac12930b0","abstract_canon_sha256":"76681aa380ce984adc84240aa8a02eaead0bec3c762408e8562eb00a459bd132"},"schema_version":"1.0"},"canonical_sha256":"3ff8206d227a629fe02981c06d144703e889d5528915a2ace920806aaad77c2a","source":{"kind":"arxiv","id":"1612.00767","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1612.00767","created_at":"2026-05-18T00:55:33Z"},{"alias_kind":"arxiv_version","alias_value":"1612.00767v2","created_at":"2026-05-18T00:55:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.00767","created_at":"2026-05-18T00:55:33Z"},{"alias_kind":"pith_short_12","alias_value":"H74CA3JCPJRJ","created_at":"2026-05-18T12:30:19Z"},{"alias_kind":"pith_short_16","alias_value":"H74CA3JCPJRJ7YBJ","created_at":"2026-05-18T12:30:19Z"},{"alias_kind":"pith_short_8","alias_value":"H74CA3JC","created_at":"2026-05-18T12:30:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:H74CA3JCPJRJ7YBJQHAG2FCHAP","target":"record","payload":{"canonical_record":{"source":{"id":"1612.00767","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-12-02T17:43:33Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"fe4e84fd7aa08533eb6d89071c41f55e5ef664a761bb7e487ec42a1ac12930b0","abstract_canon_sha256":"76681aa380ce984adc84240aa8a02eaead0bec3c762408e8562eb00a459bd132"},"schema_version":"1.0"},"canonical_sha256":"3ff8206d227a629fe02981c06d144703e889d5528915a2ace920806aaad77c2a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:55:33.770497Z","signature_b64":"AVgnEiVwVCtw224fZdAwzvsH9NU1I/up5Uz123lUi5ioaT0JqXW12Yyeyq4/+qBXbhZPTiWxEcznTpsSV7U3Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3ff8206d227a629fe02981c06d144703e889d5528915a2ace920806aaad77c2a","last_reissued_at":"2026-05-18T00:55:33.769878Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:55:33.769878Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1612.00767","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":"2026-05-18T00:55:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b+tl+2QNwVe7gujT+WtmC3pwLvTSh0zSCFvx1TWNU9e0wPLSI2+5WKhnKufFp9qGn1UoJ9JaNrjXiN+B5BRQAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-12T08:31:09.933103Z"},"content_sha256":"7403bf0890409151751c0de9540c477978f2a31c4a66590c376deb283c4cf81c","schema_version":"1.0","event_id":"sha256:7403bf0890409151751c0de9540c477978f2a31c4a66590c376deb283c4cf81c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:H74CA3JCPJRJ7YBJQHAG2FCHAP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Asynchronous Stochastic Gradient MCMC with Elastic Coupling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"stat.ML","authors_text":"Aaron Klein, Frank Hutter, Jost Tobias Springenberg, Stefan Falkner","submitted_at":"2016-12-02T17:43:33Z","abstract_excerpt":"We consider parallel asynchronous Markov Chain Monte Carlo (MCMC) sampling for problems where we can leverage (stochastic) gradients to define continuous dynamics which explore the target distribution. We outline a solution strategy for this setting based on stochastic gradient Hamiltonian Monte Carlo sampling (SGHMC) which we alter to include an elastic coupling term that ties together multiple MCMC instances. The proposed strategy turns inherently sequential HMC algorithms into asynchronous parallel versions. First experiments empirically show that the resulting parallel sampler significantl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.00767","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":"2026-05-18T00:55:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gfc/NIbNzMfjtds5Is4l60QTp/WOhxkW4E6n5hUMr4ZVxGlkJyODJqwYDHn/DuDOD59zPLO8ucmodidzXUiKBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-12T08:31:09.933457Z"},"content_sha256":"f2faac04df77698f657cb81487ea97d78ba1c42dc80ba032cf0123c930bc8056","schema_version":"1.0","event_id":"sha256:f2faac04df77698f657cb81487ea97d78ba1c42dc80ba032cf0123c930bc8056"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/H74CA3JCPJRJ7YBJQHAG2FCHAP/bundle.json","state_url":"https://pith.science/pith/H74CA3JCPJRJ7YBJQHAG2FCHAP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/H74CA3JCPJRJ7YBJQHAG2FCHAP/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":"2026-06-12T08:31:09Z","links":{"resolver":"https://pith.science/pith/H74CA3JCPJRJ7YBJQHAG2FCHAP","bundle":"https://pith.science/pith/H74CA3JCPJRJ7YBJQHAG2FCHAP/bundle.json","state":"https://pith.science/pith/H74CA3JCPJRJ7YBJQHAG2FCHAP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/H74CA3JCPJRJ7YBJQHAG2FCHAP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:H74CA3JCPJRJ7YBJQHAG2FCHAP","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":"76681aa380ce984adc84240aa8a02eaead0bec3c762408e8562eb00a459bd132","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-12-02T17:43:33Z","title_canon_sha256":"fe4e84fd7aa08533eb6d89071c41f55e5ef664a761bb7e487ec42a1ac12930b0"},"schema_version":"1.0","source":{"id":"1612.00767","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1612.00767","created_at":"2026-05-18T00:55:33Z"},{"alias_kind":"arxiv_version","alias_value":"1612.00767v2","created_at":"2026-05-18T00:55:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.00767","created_at":"2026-05-18T00:55:33Z"},{"alias_kind":"pith_short_12","alias_value":"H74CA3JCPJRJ","created_at":"2026-05-18T12:30:19Z"},{"alias_kind":"pith_short_16","alias_value":"H74CA3JCPJRJ7YBJ","created_at":"2026-05-18T12:30:19Z"},{"alias_kind":"pith_short_8","alias_value":"H74CA3JC","created_at":"2026-05-18T12:30:19Z"}],"graph_snapshots":[{"event_id":"sha256:f2faac04df77698f657cb81487ea97d78ba1c42dc80ba032cf0123c930bc8056","target":"graph","created_at":"2026-05-18T00:55:33Z","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":"We consider parallel asynchronous Markov Chain Monte Carlo (MCMC) sampling for problems where we can leverage (stochastic) gradients to define continuous dynamics which explore the target distribution. We outline a solution strategy for this setting based on stochastic gradient Hamiltonian Monte Carlo sampling (SGHMC) which we alter to include an elastic coupling term that ties together multiple MCMC instances. The proposed strategy turns inherently sequential HMC algorithms into asynchronous parallel versions. First experiments empirically show that the resulting parallel sampler significantl","authors_text":"Aaron Klein, Frank Hutter, Jost Tobias Springenberg, Stefan Falkner","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-12-02T17:43:33Z","title":"Asynchronous Stochastic Gradient MCMC with Elastic Coupling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.00767","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":"sha256:7403bf0890409151751c0de9540c477978f2a31c4a66590c376deb283c4cf81c","target":"record","created_at":"2026-05-18T00:55:33Z","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":"76681aa380ce984adc84240aa8a02eaead0bec3c762408e8562eb00a459bd132","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-12-02T17:43:33Z","title_canon_sha256":"fe4e84fd7aa08533eb6d89071c41f55e5ef664a761bb7e487ec42a1ac12930b0"},"schema_version":"1.0","source":{"id":"1612.00767","kind":"arxiv","version":2}},"canonical_sha256":"3ff8206d227a629fe02981c06d144703e889d5528915a2ace920806aaad77c2a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3ff8206d227a629fe02981c06d144703e889d5528915a2ace920806aaad77c2a","first_computed_at":"2026-05-18T00:55:33.769878Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:55:33.769878Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AVgnEiVwVCtw224fZdAwzvsH9NU1I/up5Uz123lUi5ioaT0JqXW12Yyeyq4/+qBXbhZPTiWxEcznTpsSV7U3Dg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:55:33.770497Z","signed_message":"canonical_sha256_bytes"},"source_id":"1612.00767","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7403bf0890409151751c0de9540c477978f2a31c4a66590c376deb283c4cf81c","sha256:f2faac04df77698f657cb81487ea97d78ba1c42dc80ba032cf0123c930bc8056"],"state_sha256":"bf7706cb14365146595e50aad485c88b1a4ad6758dd633d0d77c0c072d34baec"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CJeVZyYVDHG68LzVPjVHf9v8Lg8SXlB5MXP3SIWDRBDBeINqCsJUdzp4PyIpDOobFr604Dcx/sFxxNVOAzOSBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-12T08:31:09.935426Z","bundle_sha256":"9c652b89296ea92b4cb6c164ed99654b2627feee15c984e5c412b8e8a2e823c9"}}