Variational Inference

Stein Variational Evolution Strategies UAI 2025 Theoretical Convergence Guarantees for Variational Autoencoders AISTATS 2025 Towards Fair Graph Learning without Demographic Information AISTATS 2025 Unified Variational and Physics-aware Model for Room Impulse Response Estimation Interspeech 2025 Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix AISTATS 2025 Variational Inference on the Boolean Hypercube with the Quantum Entropy AISTATS 2025 Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling UAI 2025 Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference AISTATS 2025 Well-Defined Function-Space Variational Inference in Bayesian Neural Networks via Regularized KL-Divergence UAI 2025 Amortized Variational Inference: When and Why? UAI 2024 Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm NeurIPS 2024 EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning ACML 2024 Exploring Conditional Variational Mechanism to Pinyin Input Method for Addressing One-to-Many Mappings in Low-Resource Scenarios ACL 2024 Functional Wasserstein Bridge Inference for Bayesian Deep Learning UAI 2024 Functional Wasserstein Variational Policy Optimization UAI 2024 Poisson Variational Autoencoder NeurIPS 2024 S$2$AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic ICLR 2024 Sample Average Approximation for Black-Box Variational Inference UAI 2024 Variational Resampling AISTATS 2024 Benchmarking Constraint Inference in Inverse Reinforcement Learning ICLR 2023 Cell Variational Information Bottleneck Network ACML 2023 Differentiable Random Partition Models NeurIPS 2023 Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory NeurIPS 2023 Generative Label Enhancement with Gaussian Mixture and Partial Ranking AAAI 2023 GFlowNets and variational inference ICLR 2023