langevin dynamics

128 papers

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Also known as

LMC LD LA ULA

Co-occurring keywords

markov chain monte carlo (724) stochastic gradient (296) bayesian inference (1904) energy-based model (248) posterior sampling (152) generative model (2889) variational inference (2069) stochastic gradient descent (1088) sampling algorithm (130) wasserstein distance (417)

Papers

Exploring Non-Convex Discrete Energy Landscapes: An Efficient Langevin-Like Sampler with Replica Exchange AAAI 2026

Score-Based Diffusion Models in Function Space JMLR 2025

Consistency Posterior Sampling for Diverse Image Synthesis CVPR 2025

UniFORM: Towards Unified Framework for Anomaly Detection on Graphs AAAI 2025

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin ICCV 2025

Langevin Multiplicative Weights Update with Applications in Polynomial Portfolio Management AAAI 2025

Exponential-Family Harmoniums with Neural Sufficient Statistics AAAI 2025

Robust Approximate Sampling via Stochastic Gradient Barker Dynamics AISTATS 2024

Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm COLT 2024

PureGen: Universal Data Purification for Train-Time Poison Defense via Generative Model Dynamics NIPS 2024

A Dynamic Kernel Prior Model for Unsupervised Blind Image Super-Resolution CVPR 2024

Improved Particle Approximation Error for Mean Field Neural Networks NIPS 2024

Penalized Overdamped and Underdamped Langevin Monte Carlo Algorithms for Constrained Sampling JMLR 2024

Fisher information dissipation for time-inhomogeneous stochastic differential equations JMLR 2024

Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning NIPS 2024

The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank AAAI 2024

Multi-objective Optimization via Wasserstein-Fisher-Rao Gradient Flow AISTATS 2024

Score-based 3D molecule generation with neural fields NIPS 2024

Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo AISTATS 2024

Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets JMLR 2024

On the Computational Complexity of Metropolis-Adjusted Langevin Algorithms for Bayesian Posterior Sampling JMLR 2024

Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference NIPS 2024

A Bayesian Approach to Data Point Selection NIPS 2024

Microcanonical Hamiltonian Monte Carlo JMLR 2023

MDM: Molecular Diffusion Model for 3D Molecule Generation AAAI 2023