Bayesian Inference

A Variational Perspective on Generative Protein Fitness Optimization ICML 2025 Backward Filtering Forward Guiding JMLR 2025 BARK: A Fully Bayesian Tree Kernel for Black-box Optimization ICML 2025 BARNN: A Bayesian Autoregressive and Recurrent Neural Network ICML 2025 BayesCNS: A Unified Bayesian Approach to Address Cold Start and Non-Stationarity in Search Systems at Scale AAAI 2025 Bayesian Active Learning for Bivariate Causal Discovery ICML 2025 Bayesian Analysis of Combinatorial Gaussian Process Bandits ICLR 2025 Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models ICML 2025 Bayesian Circular Regression with von Mises Quasi-Processes AISTATS 2025 Bayesian Code Diffusion for Efficient Automatic Deep Learning Program Optimization OSDI 2025 Bayesian Data Sketching for Varying Coefficient Regression Models JMLR 2025 Bayesian Experimental Design Via Contrastive Diffusions ICLR 2025 Bayesian Gaussian Process ODEs via Double Normalizing Flows AISTATS 2025 Bayesian Image Regression with Soft-thresholded Conditional Autoregressive Prior ICLR 2025 Bayesian Inference for Correlated Human Experts and Classifiers ICML 2025 Bayesian Inference in Recurrent Explicit Duration Switching Linear Dynamical Systems AISTATS 2025 Bayesian-Inspired Space-Time Superpixels ICCV 2025 Bayesian Low-Rank Learning (Bella): A Practical Approach to Bayesian Neural Networks AAAI 2025 Bayesian Multi-Group Gaussian Process Models for Heterogeneous Group-Structured Data JMLR 2025 Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks ICML 2025 Bayesian Off-Policy Evaluation and Learning for Large Action Spaces AISTATS 2025 Bayesian Optimal Latent Projection for Noisy Image Restoration WACV 2025 Bayesian Optimization for Controlled Image Editing via LLMs ACL 2025 Bayesian Optimization for Unknown Cost-Varying Variable Subsets with No-Regret Costs AAAI 2025 Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds ICML 2025