mcmc sampling

A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning AAAI 2025 Optimal Scaling for the Proximal Langevin Algorithm in High Dimensions JMLR 2024 Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains (Extended Abstract) IJCAI 2024 A Dynamical System View of Langevin-Based Non-Convex Sampling NeurIPS 2023 Discrete Langevin Samplers via Wasserstein Gradient Flow AISTATS 2023 Distance-to-Set Priors and Constrained Bayesian Inference AISTATS 2023 Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach NeurIPS 2023 Unbiased constrained sampling with Self-Concordant Barrier Hamiltonian Monte Carlo NeurIPS 2023 Common Failure Modes of Subcluster-based Sampling in Dirichlet Process Gaussian Mixture Models - and a Deep-learning Solution AISTATS 2022 Discrete Probabilistic Inverse Optimal Transport ICML 2022 Joint 3D Object Detection and Tracking Using Spatio-Temporal Representation of Camera Image and LiDAR Point Clouds AAAI 2022 Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling JMLR 2022 Sampling in Dirichlet Process Mixture Models for Clustering Streaming Data AISTATS 2022 Evaluating the Implicit Midpoint Integrator for Riemannian Hamiltonian Monte Carlo ICML 2021 Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling NeurIPS 2021 Identifying Norms from Observation Using MCMC Sampling IJCAI 2021 Learning Energy-Based Models by Diffusion Recovery Likelihood ICLR 2021 No MCMC for me: Amortized sampling for fast and stable training of energy-based models ICLR 2021 On the Convergence of Hamiltonian Monte Carlo with Stochastic Gradients ICML 2021 Optimal Underdamped Langevin MCMC Method NeurIPS 2021 Pseudo-Marginal Hamiltonian Monte Carlo JMLR 2021 Aggregated Gradient Langevin Dynamics AAAI 2020 Learning Latent Space Energy-Based Prior Model NeurIPS 2020 On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models AAAI 2020 Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach AISTATS 2019