Probabilistic Modeling

Gaussian Differential Privacy on Riemannian Manifolds NeurIPS 2023 Generalizable Neural Fields as Partially Observed Neural Processes ICCV 2023 Generalized Belief Transport NeurIPS 2023 Generative Augmented Flow Networks ICLR 2023 Generative Label Enhancement with Gaussian Mixture and Partial Ranking AAAI 2023 Geometric Neural Diffusion Processes NeurIPS 2023 GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies NeurIPS 2023 GFlowNet Foundations JMLR 2023 Global Identifiability of ℓ_1-based Dictionary Learning via Matrix Volume Optimization NeurIPS 2023 Global Perception Based Autoregressive Neural Processes ICCV 2023 GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks ICLR 2023 Graph Denoising Diffusion for Inverse Protein Folding NeurIPS 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 High Fidelity Image Counterfactuals with Probabilistic Causal Models ICML 2023 HuManiFlow: Ancestor-Conditioned Normalising Flows on SO(3) Manifolds for Human Pose and Shape Distribution Estimation CVPR 2023 Identification of Nonlinear Latent Hierarchical Models NeurIPS 2023 Improved Discretization Analysis for Underdamped Langevin Monte Carlo COLT 2023 Improving Diachronic Word Sense Induction with a Nonparametric Bayesian method ACL 2023 Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation AISTATS 2023 Inference for probabilistic dependency graphs UAI 2023 Influence-Aware Attention for Multivariate Temporal Point Processes CLeaR 2023 Input uncertainty propagation through trained neural networks ICML 2023 Inverse-Reference Priors for Fisher Regularization of Bayesian Neural Networks AAAI 2023 Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network NeurIPS 2023