particle method

Learning Latent Energy-Based Models via Interacting Particle Langevin Dynamics UAI 2026 Diffusion-Based Particle-DETR for BEV Perception WACV 2025 Guiding Time-Varying Generative Models with Natural Gradients on Exponential Family Manifold UAI 2025 Momentum Particle Maximum Likelihood ICML 2024 Multi-objective Optimization via Wasserstein-Fisher-Rao Gradient Flow AISTATS 2024 Particle Semi-Implicit Variational Inference NeurIPS 2024 A Finite-Particle Convergence Rate for Stein Variational Gradient Descent NeurIPS 2023 Learning Rate Free Sampling in Constrained Domains NeurIPS 2023 Particle-based Variational Inference with Generalized Wasserstein Gradient Flow NeurIPS 2023 Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent NeurIPS 2023 Accurate Quantization of Measures via Interacting Particle-based Optimization ICML 2022 Centroid Approximation for Bootstrap: Improving Particle Quality at Inference ICML 2022 Grassmann Stein Variational Gradient Descent AISTATS 2022 Kernel Stein Discrepancy Descent ICML 2021 Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers AISTATS 2019 Interacting Particle Markov Chain Monte Carlo ICML 2016 Provable Bayesian Inference via Particle Mirror Descent AISTATS 2016 Proteins, Particles, and Pseudo-Max-Marginals: A Submodular Approach ICML 2015 Sequential Monte Carlo for Graphical Models NeurIPS 2014 Particle-based Variational Inference for Continuous Systems NeurIPS 2009