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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

Decentralized Langevin Dynamics for Bayesian Learning NIPS 2020
Robust Reinforcement Learning via Adversarial training with Langevin Dynamics NIPS 2020
Denoising Diffusion Probabilistic Models NIPS 2020
Generative Modeling by Estimating Gradients of the Data Distribution NIPS 2019
The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects ICML 2019
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates NIPS 2019
Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction NIPS 2019
Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models ICML 2019
Variational Annealing of GANs: A Langevin Perspective ICML 2019
Underdamped Langevin MCMC: A non-asymptotic analysis COLT 2018
Mirrored Langevin Dynamics NIPS 2018
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization NIPS 2018
Learning Descriptor Networks for 3D Shape Synthesis and Analysis CVPR 2018
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem COLT 2018
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks NIPS 2017
Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for Markov Chain Monte Carlo ICML 2017
Quantifying the accuracy of approximate diffusions and Markov chains AISTATS 2017
A Divergence Bound for Hybrids of MCMC and Variational Inference and an Application to Langevin Dynamics and SGVI ICML 2017
A Theory of Generative ConvNet ICML 2016
Stochastic Quasi-Newton Langevin Monte Carlo ICML 2016
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators NIPS 2015
Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling NIPS 2015
Finite-Time Analysis of Projected Langevin Monte Carlo NIPS 2015
Bayesian Sampling Using Stochastic Gradient Thermostats NIPS 2014
Fast Sampling-Based Inference in Balanced Neuronal Networks NIPS 2014