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The Euler discretization of the Langevin stochastic differential equation (SDE) is known to be unstable in a precise sense, when the potential $U$ is superlinear, i.e. $\\liminf_{\\Vert x \\Vert\\to+\\infty} \\Vert \\nabla U(x) \\Vert / \\Vert x \\Vert = +\\infty$. Based on previous works on the taming of superlinear drift coefficients for SDEs, we introduce the Tame"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1710.05559","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-10-16T08:32:28Z","cross_cats_sorted":[],"title_canon_sha256":"9106604459a8fbd1413882c5d958eaa283723361633aa68fbc6600755641791a","abstract_canon_sha256":"204ac0da518d9d55164086a87a7c0e7f5d2e633b7090910ed1cc26c816d981e2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:02.448642Z","signature_b64":"kqZaWlKLqsFiZI2bJStQVHqrY/TqQRiG1XG7dPIWF6zk8y6iL8U1RixJlGS0XWbEAwkyNwXX5CZ2ECx5FseVCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"92a5e40d3f6bcbf46dae83572cea1e0635f470302b46f23bbe2ae390673e98a4","last_reissued_at":"2026-05-18T00:00:02.448160Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:02.448160Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The Tamed Unadjusted Langevin Algorithm","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Alain Durmus, \\'Eric Moulines, Nicolas Brosse, Sotirios Sabanis","submitted_at":"2017-10-16T08:32:28Z","abstract_excerpt":"In this article, we consider the problem of sampling from a probability measure $\\pi$ having a density on $\\mathbb{R}^d$ known up to a normalizing constant, $x\\mapsto \\mathrm{e}^{-U(x)} / \\int_{\\mathbb{R}^d} \\mathrm{e}^{-U(y)} \\mathrm{d} y$. 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