langevin dynamics

Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization NeurIPS 2020 Decentralized Langevin Dynamics for Bayesian Learning NeurIPS 2020 Denoising Diffusion Probabilistic Models NeurIPS 2020 Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev NeurIPS 2020 Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC NeurIPS 2020 Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise ICML 2020 Generalization bound of globally optimal non-convex neural network training: Transportation map estimation by infinite dimensional Langevin dynamics NeurIPS 2020 On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models AAAI 2020 On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method NeurIPS 2020 Posterior sampling strategies based on discretized stochastic differential equations for machine learning applications JMLR 2020 Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm NeurIPS 2020 Robust Reinforcement Learning via Adversarial training with Langevin Dynamics NeurIPS 2020 Sharpened Generalization Bounds based on Conditional Mutual Information and an Application to Noisy, Iterative Algorithms NeurIPS 2020 Source Separation with Deep Generative Priors ICML 2020 Stein Self-Repulsive Dynamics: Benefits From Past Samples NeurIPS 2020 Stochastic Approximate Gradient Descent via the Langevin Algorithm AAAI 2020 Stochastic Normalizing Flows NeurIPS 2020 Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling NeurIPS 2020 Generative Modeling by Estimating Gradients of the Data Distribution NeurIPS 2019 Learning Protein Structure with a Differentiable Simulator ICLR 2019 Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models ICML 2019 Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction NeurIPS 2019 Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates NeurIPS 2019 The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects ICML 2019 Variational Annealing of GANs: A Langevin Perspective ICML 2019