Bayesian & Probabilistic

Functional Wasserstein Variational Policy Optimization UAI 2024 Fundamental Limits of Non-Linear Low-Rank Matrix Estimation COLT 2024 Gated Inference Network: Inference and Learning State-Space Models NeurIPS 2024 Gaussian Cooling and Dikin Walks: The Interior-Point Method for Logconcave Sampling COLT 2024 Gaussian Processes on Cellular Complexes ICML 2024 Gaussian Process Neural Additive Models AAAI 2024 General bounds on the quality of Bayesian coresets NeurIPS 2024 Generalized Bradley-Terry Models for Score Estimation from Paired Comparisons AAAI 2024 Generative Conditional Distributions by Neural (Entropic) Optimal Transport ICML 2024 Generative Flow Networks as Entropy-Regularized RL AISTATS 2024 Geometric No-U-Turn Samplers: Concepts and Evaluation PGM 2024 Graphical Dirichlet Process for Clustering Non-Exchangeable Grouped Data JMLR 2024 Graphical Multioutput Gaussian Process with Attention ICLR 2024 Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification ICML 2024 Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models NeurIPS 2024 HHD-GP: Incorporating Helmholtz-Hodge Decomposition into Gaussian Processes for Learning Dynamical Systems NeurIPS 2024 Hodge-Compositional Edge Gaussian Processes AISTATS 2024 How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression UAI 2024 Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty ICLR 2024 Hyperparameter-Free Approach for Faster Minimum Bayes Risk Decoding ACL 2024 Identifying and Addressing Disparities in Public Libraries with Bayesian Latent Variable Modeling AAAI 2024 Idiographic Personality Gaussian Process for Psychological Assessment NeurIPS 2024 Image Background Serves as Good Proxy for Out-of-distribution Data ICLR 2024 Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control ICLR 2024 Implicit Gaussian process representation of vector fields over arbitrary latent manifolds ICLR 2024