Bayesian & Probabilistic

Scalable Bayesian Meta-Learning through Generalized Implicit Gradients AAAI 2023 Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes AISTATS 2023 Scalable high-dimensional Bayesian varying coefficient models with unknown within-subject covariance JMLR 2023 Scale-Invariant Infinite Hierarchical Topic Model ACL 2023 ScanDMM: A Deep Markov Model of Scanpath Prediction for 360deg Images CVPR 2023 Score-based Data Assimilation NeurIPS 2023 Score-Based Diffusion Models as Principled Priors for Inverse Imaging ICCV 2023 Semiparametric Inference Using Fractional Posteriors JMLR 2023 Semi-supervised Community Detection via Structural Similarity Metrics ICLR 2023 Semi-Supervised Deep Regression with Uncertainty Consistency and Variational Model Ensembling via Bayesian Neural Networks AAAI 2023 Separate but Equal: Equality in Belief Propagation for Single Cycle Graphs AAAI 2023 Sequential Monte Carlo Learning for Time Series Structure Discovery ICML 2023 Sharp Calibrated Gaussian Processes NeurIPS 2023 Single Image Depth Prediction Made Better: A Multivariate Gaussian Take CVPR 2023 SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals AISTATS 2023 Sparse Markov Models for High-dimensional Inference JMLR 2023 Sparse Maximum Margin Learning from Multimodal Human Behavioral Patterns AAAI 2023 Sparse Spectral Bayesian Permanental Process with Generalized Kernel AISTATS 2023 Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck AISTATS 2023 Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes ICML 2023 Statistical Efficiency of Score Matching: The View from Isoperimetry ICLR 2023 Statistical Guarantees for Consensus Clustering ICLR 2023 Statistical Inference for Noisy Incomplete Binary Matrix JMLR 2023 Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms ICLR 2023 Stimulus Verification Is a Universal and Effective Sampler in Multi-Modal Human Trajectory Prediction CVPR 2023