:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Cordero-Encinar, Paula, Akyildiz, O. Deniz, Duncan, Andrew B.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Probability Computation
Online Access:	https://arxiv.org/abs/2502.09306
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Diffusion Path Samplers via Sequential Monte Carlo
by: Young, James Matthew, et al.
Published: (2026)

Proximal Interacting Particle Langevin Algorithms
by: Encinar, Paula Cordero, et al.
Published: (2024)

Diffusion annealed Langevin dynamics: a theoretical study
by: Cattiaux, Patrick, et al.
Published: (2025)

Sampling by averaging: A multiscale approach to score estimation
by: Cordero-Encinar, Paula, et al.
Published: (2025)

Kinetic Interacting Particle Langevin Monte Carlo
by: Oliva, Paul Felix Valsecchi, et al.
Published: (2024)

Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation
by: Akyildiz, Ö. Deniz, et al.
Published: (2023)

Non-asymptotic estimates for accelerated high order Langevin Monte Carlo algorithms
by: Neufeld, Ariel, et al.
Published: (2024)

Non-asymptotic analysis of Langevin-type Monte Carlo algorithms
by: Nakakita, Shogo
Published: (2023)

Gaussian entropic optimal transport: Schrödinger bridges and the Sinkhorn algorithm
by: Akyildiz, O. Deniz, et al.
Published: (2024)

Regime-Switching Langevin Monte Carlo Algorithms
by: Wang, Xiaoyu, et al.
Published: (2025)

Parallelized Midpoint Randomization for Langevin Monte Carlo
by: Yu, Lu, et al.
Published: (2024)

Soft Specialists: $α$-Rényi Ensembles for Uncertainty-Aware LLM Post-Training
by: Cordero-Encinar, Paula, et al.
Published: (2026)

Certified Self-Consistency: Statistical Guarantees and Test-Time Training for Reliable Reasoning in LLMs
by: Cordero-Encinar, Paula, et al.
Published: (2025)

User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient
by: Dalalyan, Arnak S., et al.
Published: (2017)

High-Order Langevin Monte Carlo Algorithms
by: Dang, Thanh, et al.
Published: (2025)

Accelerating Langevin Monte Carlo Sampling: A Large Deviations Analysis
by: Yao, Nian, et al.
Published: (2025)

Learning Latent Variable Models via Jarzynski-adjusted Langevin Algorithm
by: Cuin, James, et al.
Published: (2025)

Analysis of kinetic Langevin Monte Carlo under the stochastic exponential Euler discretization from underdamped all the way to overdamped
by: Kim, Kyurae, et al.
Published: (2025)

Efficient Stochastic Optimisation via Sequential Monte Carlo
by: Cuin, James, et al.
Published: (2026)

Non-Reversible Langevin Algorithms for Constrained Sampling
by: Du, Hengrong, et al.
Published: (2025)

Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization
by: Akyildiz, Ömer Deniz, et al.
Published: (2020)

Learning Latent Energy-Based Models via Interacting Particle Langevin Dynamics
by: Marks, Joanna, et al.
Published: (2025)

A hierarchical entropy method for the delocalization of bias in high-dimensional Langevin Monte Carlo
by: Lacker, Daniel, et al.
Published: (2025)

Sampling from multimodal distributions with warm starts: Non-asymptotic bounds for the Reweighted Annealed Leap-Point Sampler
by: Lee, Holden, et al.
Published: (2025)

Convergence of Kinetic Langevin Monte Carlo on Lie groups
by: Kong, Lingkai, et al.
Published: (2024)

Complexity of Markov Chain Monte Carlo for Generalized Linear Models
by: Chak, Martin, et al.
Published: (2025)

Non-asymptotic Analysis of Poisson randomized midpoint Langevin Monte Carlo
by: Shen, Tian, et al.
Published: (2025)

Approximating Langevin Monte Carlo with ResNet-like Neural Network architectures
by: Miranda, Charles, et al.
Published: (2023)

Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling
by: Guo, Wei, et al.
Published: (2024)

Langevin Monte-Carlo Provably Learns Depth Two Neural Nets at Any Size and Data
by: Kumar, Dibyakanti, et al.
Published: (2025)

Some aspects of robustness in modern Markov Chain Monte Carlo
by: Power, Sam, et al.
Published: (2025)

On diffusion posterior sampling via sequential Monte Carlo for zero-shot scaffolding of protein motifs
by: Young, James Matthew, et al.
Published: (2024)

A Gradient Flow Approach to Solving Inverse Problems with Latent Diffusion Models
by: Wang, Tim Y. J., et al.
Published: (2025)

Deep Optimal Sensor Placement for Black Box Stochastic Simulations
by: Cordero-Encinar, Paula, et al.
Published: (2024)

Reverse-BSDE Monte Carlo
by: Batista, Jairon H. N., et al.
Published: (2025)

On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates
by: Bruno, Stefano, et al.
Published: (2023)

Convergence of Unadjusted Langevin in High Dimensions: Delocalization of Bias
by: Chen, Yifan, et al.
Published: (2024)

Weak Functional Inequalities for Perturbed Measures
by: Cattiaux, Patrick, et al.
Published: (2026)

On the contraction properties of Sinkhorn semigroups
by: Akyildiz, O. Deniz, et al.
Published: (2025)

Optimal Scaling for the Proximal Langevin Algorithm in High Dimensions
by: Pillai, Natesh S.
Published: (2022)