Bayesian & Probabilistic

Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes ICML 2023 Function-space regularized Rényi divergences ICLR 2023 Gaussian processes at the Helm(holtz): A more fluid model for ocean currents ICML 2023 Gaussian Processes on Distributions based on Regularized Optimal Transport AISTATS 2023 Gaussian Processes with Errors in Variables: Theory and Computation JMLR 2023 Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients ICML 2023 Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks ICLR 2023 Generative Semantic Segmentation CVPR 2023 GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies NeurIPS 2023 GFlowNet-EM for Learning Compositional Latent Variable Models ICML 2023 GFlowNet Foundations JMLR 2023 GFlowNets and variational inference ICLR 2023 Gibbsian Polar Slice Sampling ICML 2023 Gradient Boosting Performs Gaussian Process Inference ICLR 2023 Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping AAAI 2023 Graph-Structured Gaussian Processes for Transferable Graph Learning NeurIPS 2023 GRASMOS: Graph Signage Model Selection for Gene Regulatory Networks AAAI 2023 Gray-Box Gaussian Processes for Automated Reinforcement Learning ICLR 2023 Guided Deep Kernel Learning UAI 2023 Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning NeurIPS 2023 Hierarchical-Hyperplane Kernels for Actively Learning Gaussian Process Models of Nonstationary Systems AISTATS 2023 Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration NeurIPS 2023 Hierarchical VAEs provide a normative account of motion processing in the primate brain NeurIPS 2023 High-Dimensional Dueling Optimization with Preference Embedding AAAI 2023 H-Likelihood Approach to Deep Neural Networks with Temporal-Spatial Random Effects for High-Cardinality Categorical Features ICML 2023