Paper Citation Record · LEDGER

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients

As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 2 inbound Pith citation observations for arXiv:2506.04878.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.04878 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:41:38.954047Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T12:38:28.920474Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-30T00:04:06.672064Z

Reference resolution

38 of 38 outbound references displayed

verified exact3
verified fuzzy24
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 18235c3d-937d-472d-aa47-bfbbf9bbe240 · outbound

This paper cites Smooth sigmoid wavelet shrinkage for non-parametric estimation.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Smooth sigmoid wavelet shrinkage for non-parametric estimation

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.609975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d858dfee-c8f9-465b-8aca-cfa3338adcb7 · outbound

This paper cites Towards a theory of non-log-concave sampling: first-order stationarity guarantees for Langevin monte carlo.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Towards a theory of non-log-concave sampling: first-order stationarity guarantees for Langevin monte carlo

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.593397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3fee2f62-cb5f-48ee-b486-7d1aab3feaca · outbound

This paper cites $L^2$-Wasserstein contraction of modified Euler schemes for SDEs with high diffusivity and applications.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients $L^2$-Wasserstein contraction of modified Euler schemes for SDEs with high diffusivity and applications

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:41:39.126280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b3f67e83-54af-4c94-be65-c9211ff7cc04 · outbound

This paper cites On stochastic gradient Langevin dynamics with dependent data streams in the logconcave case.Bernoulli, 27(1):1–33, 2021.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients On stochastic gradient Langevin dynamics with dependent data streams in the logconcave case.Bernoulli, 27(1):1–33, 2021

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T10:41:38.232387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09e3a012-ac5e-4ef8-bee5-9236508de9f7 · outbound

This paper cites The tamed unadjusted Langevin algorithm.Stochastic Processes and their Applications, 129(10):3638–3663, 2019.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients The tamed unadjusted Langevin algorithm.Stochastic Processes and their Applications, 129(10):3638–3663, 2019

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.566830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ce4f4d21-398b-404b-9d07-d60191ad6b38 · outbound

This paper cites On Stochastic Gradient Langevin Dynamics with Dependent Data Streams: The Fully Nonconvex Case.SIAM Journal on Mathematics of Data Science, 3(3):959–986, 2021.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients On Stochastic Gradient Langevin Dynamics with Dependent Data Streams: The Fully Nonconvex Case.SIAM Journal on Mathematics of Data Science, 3(3):959–986, 2021

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.550501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a8d5eb80-96da-41d2-92df-cd7d237dbb78 · outbound

This paper cites Sharp convergence rates for Langevin dynamics in the nonconvex setting.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Sharp convergence rates for Langevin dynamics in the nonconvex setting

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T10:41:38.559333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c45844c-b340-4f2d-b3a1-ba8497db592b · outbound

This paper cites Analysis of Langevin Monte Carlo from Poincar\'e to Log-Sobolev.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Analysis of Langevin Monte Carlo from Poincar\'e to Log-Sobolev

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T10:41:38.622839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bac5a9e7-8592-49a7-acd1-f4419d6e4473 · outbound

This paper cites an unresolved cited work.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:41:39.534590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 17aeffc2-38a8-471a-b1b4-e7ba90ea7096 · outbound

This paper cites Nonasymptotic convergence analysis for the unadjusted Langevin algorithm.The Annals of Applied Probability, 27(3):1551–1587, 2017.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Nonasymptotic convergence analysis for the unadjusted Langevin algorithm.The Annals of Applied Probability, 27(3):1551–1587, 2017

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.517267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6015fffc-1694-4d08-a035-3e56e24adc4e · outbound

This paper cites High-dimensional Bayesian inference via the unadjusted Langevin algorithm.Bernoulli, 25(4A):2854–2882, 2019.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients High-dimensional Bayesian inference via the unadjusted Langevin algorithm.Bernoulli, 25(4A):2854–2882, 2019

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.498816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9fe2a93e-4464-418b-9150-7107ec67159d · outbound

This paper cites Convergence of Langevin Monte Carlo in chi-squared and R ´enyi divergence.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Convergence of Langevin Monte Carlo in chi-squared and R ´enyi divergence

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.482319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f9fff660-5425-4663-b5c6-a81fe6abcf56 · outbound

This paper cites On the diffeomorphisms of Euclidean space.The American Mathematical Monthly, 79(7):755–759, 1972.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients On the diffeomorphisms of Euclidean space.The American Mathematical Monthly, 79(7):755–759, 1972

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.467370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 31b9e2a2-5577-44d0-97f9-c8517c05cdb3 · outbound

This paper cites an unresolved cited work.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:41:39.451502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation adbc135c-7a26-4f62-a936-7a7ae750774d · outbound

This paper cites an unresolved cited work.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:41:39.433488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3fbe3dcd-e108-4512-9ffd-5c19d920e30c · outbound

This paper cites Laplace’s method revisited: weak convergence of probability measures.The Annals of Probability, 8(6):1177–1182, 1980.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Laplace’s method revisited: weak convergence of probability measures.The Annals of Probability, 8(6):1177–1182, 1980

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.415788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 534ca0e9-6fa9-4b66-bb96-62d2464dfa76 · outbound

This paper cites Kinetic Langevin MCMC Sampling Without Gradient Lipschitz Continuity -- the Strongly Convex Case.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Kinetic Langevin MCMC Sampling Without Gradient Lipschitz Continuity -- the Strongly Convex Case

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:41:39.070117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 561655b6-37df-4f00-b368-b33afef7e078 · outbound

This paper cites an unresolved cited work.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Unresolved cited work

Reference 18

Resolution: verified exact; doi, observed 2026-08-07T10:41:38.994418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7904cdb1-862b-4104-be32-c518a2161159 · outbound

This paper cites Non-asymptotic estimates for TUSLA algorithm for non-convex learning with applications to neural networks with ReLU activation function.IMA Journal of Numerical Analysis, 2023.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Non-asymptotic estimates for TUSLA algorithm for non-convex learning with applications to neural networks with ReLU activation function.IMA Journal of Numerical Analysis, 2023

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.398306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cd173d8f-21a7-4ee3-8153-b12247ceb557 · outbound

This paper cites Langevin dynamics based algorithm e-TH ε O POULA for stochastic optimization problems with discontinuous stochastic gradient.Mathematics of Operations Research, 2024.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Langevin dynamics based algorithm e-TH ε O POULA for stochastic optimization problems with discontinuous stochastic gradient.Mathematics of Operations Research, 2024

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.382224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5f796b75-9b91-4cda-981b-cd27960ead68 · outbound

This paper cites Taming neural networks with tusla: Nonconvex learning via adaptive stochastic gradient langevin algorithms.SIAM Journal on Mathematics of Data Science, 5(2):323–345, 2023.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Taming neural networks with tusla: Nonconvex learning via adaptive stochastic gradient langevin algorithms.SIAM Journal on Mathematics of Data Science, 5(2):323–345, 2023

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.365938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b990311f-4bef-456a-a917-5829fb844886 · outbound

This paper cites Tamed Langevin sampling under weaker conditions.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Tamed Langevin sampling under weaker conditions

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T10:41:38.870584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 710d862c-39c6-45ed-ae9c-ecb289fae808 · outbound

This paper cites Taming under isoperimetry.Stochastic Processes and their Applications, page 104684, 2025.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Taming under isoperimetry.Stochastic Processes and their Applications, page 104684, 2025

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T10:41:38.875472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bffb13c-cda5-477a-ba49-8301c47845a5 · outbound

This paper cites Improved bounds for discretization of Langevin diffusions: Near-optimal rates without convexity.Bernoulli, 28(3): 1577–1601, 2022.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Improved bounds for discretization of Langevin diffusions: Near-optimal rates without convexity.Bernoulli, 28(3): 1577–1601, 2022

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.339168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c19bf098-4d61-4982-8f36-677ed337a6b3 · outbound

This paper cites Supplement to ”Improved bounds for discretization of Langevin diffusions: Near-optimal rates without convexity”.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Supplement to ”Improved bounds for discretization of Langevin diffusions: Near-optimal rates without convexity”

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.322547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 54ab32b3-565d-4a2a-94ee-119c11889885 · outbound

This paper cites Towards a complete analysis of Langevin Monte Carlo: Beyond poincar´e inequality.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Towards a complete analysis of Langevin Monte Carlo: Beyond poincar´e inequality

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.307125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c7a484bb-bab7-4bcc-af52-4ec78f64d2b8 · outbound

This paper cites Non-asymptotic estimates for accelerated high order Langevin Monte Carlo algorithms.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Non-asymptotic estimates for accelerated high order Langevin Monte Carlo algorithms

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T10:41:38.895788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c5c6129-821d-4b97-87be-2b906585bc9e · outbound

This paper cites Non-asymptotic convergence bounds for modified tamed unadjusted Langevin algorithm in non-convex setting.Journal of Mathematical Analysis and Applications, 543(1):128892, 2025.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Non-asymptotic convergence bounds for modified tamed unadjusted Langevin algorithm in non-convex setting.Journal of Mathematical Analysis and Applications, 543(1):128892, 2025

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.291354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 68af1fa0-18dc-4e40-8d45-9f89de98cf51 · outbound

This paper cites Wasserstein continuity of entropy and outer bounds for interference channels.IEEE Transactions on Information Theory, 62(7):3992–4002, 2016.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Wasserstein continuity of entropy and outer bounds for interference channels.IEEE Transactions on Information Theory, 62(7):3992–4002, 2016

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.273574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 875872cd-e330-4421-a4c8-0f3fc077ca8c · outbound

This paper cites Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.255654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c6d4e147-f504-49a6-bf8f-f3b1c8780cf8 · outbound

This paper cites Information theoretic proofs of entropy power inequalities.IEEE transactions on information theory, 57(1):33–55, 2010.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Information theoretic proofs of entropy power inequalities.IEEE transactions on information theory, 57(1):33–55, 2010

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.238067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c9eb23db-9b25-41ae-959e-3fe67312dc6f · outbound

This paper cites A note on tamed Euler approximations.Electron.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients A note on tamed Euler approximations.Electron

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.222265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4bfbb8c7-2550-49aa-85d4-489cd1bae7fc · outbound

This paper cites Euler approximations with varying coefficients: the case of superlinearly growing diffusion coefficients.Ann.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Euler approximations with varying coefficients: the case of superlinearly growing diffusion coefficients.Ann

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.206721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 76ff6509-61cf-45fb-898b-47566b3bb1f1 · outbound

This paper cites Higher order Langevin Monte Carlo algorithm.Electronic Journal of Statistics, 13(2):3805–3850, 2019.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Higher order Langevin Monte Carlo algorithm.Electronic Journal of Statistics, 13(2):3805–3850, 2019

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.189228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 31784c12-de95-4b44-97dd-c9f2514e4e8d · outbound

This paper cites A fully data-driven approach to minimizing CVaR for portfolio of assets via SGLD with discontinuous updating.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients A fully data-driven approach to minimizing CVaR for portfolio of assets via SGLD with discontinuous updating

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T10:41:38.939069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87e690dc-3923-4542-a919-351da58670c5 · outbound

This paper cites Rapid convergence of the unadjusted Langevin algorithm: Isoperimetry suffices.Advances in neural information processing systems, 32, 2019.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Rapid convergence of the unadjusted Langevin algorithm: Isoperimetry suffices.Advances in neural information processing systems, 32, 2019

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T10:41:38.944369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cac948e8-8ec7-4e13-86ba-730f54355ed6 · outbound

This paper cites Global convergence of Langevin dynamics based algorithms for nonconvex optimization.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Global convergence of Langevin dynamics based algorithms for nonconvex optimization

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.158513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 00fd2465-42fa-438c-b48a-9752bc1dcbad · outbound

This paper cites Nonasymptotic esti- mates for stochastic gradient Langevin dynamics under local conditions in nonconvex optimization.

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients Nonasymptotic esti- mates for stochastic gradient Langevin dynamics under local conditions in nonconvex optimization

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:39.142279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation a785c0f4-b79f-4680-ae8d-b083bda93324 · inbound

Error estimates for tamed Euler and Randomized Euler schemes for SDEs with locally Lipschitz drift with applications to non-logconcave sampling and optimization cites this paper.

Error estimates for tamed Euler and Randomized Euler schemes for SDEs with locally Lipschitz drift with applications to non-logconcave sampling and optimization kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-06-30T00:04:06.673839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8cf152b2-4806-48ec-8ffe-b835a8219b9b · inbound

RELTA-SGLD: Relative-Growth Localized Taming for Nonconvex Stochastic-Gradient Langevin Learning cites this paper.

RELTA-SGLD: Relative-Growth Localized Taming for Nonconvex Stochastic-Gradient Langevin Learning kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T12:38:28.920474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.