Bayesian Inference

Semi-Implicit Variational Inference via Score Matching ICLR 2023 Semiparametrically Efficient Off-Policy Evaluation in Linear Markov Decision Processes ICML 2023 Semiparametric Inference Using Fractional Posteriors JMLR 2023 Semi-Supervised Deep Regression with Uncertainty Consistency and Variational Model Ensembling via Bayesian Neural Networks AAAI 2023 Semi-supervised learning with a principled likelihood from a generative model of data curation ICLR 2023 Sentiment as an Ordinal Latent Variable EACL 2023 Seq2Seq Surrogates of Epidemic Models to Facilitate Bayesian Inference AAAI 2023 Sequential Latent Variable Models for Few-Shot High-Dimensional Time-Series Forecasting ICLR 2023 Sequential Monte Carlo Learning for Time Series Structure Discovery ICML 2023 Seq-UPS: Sequential Uncertainty-Aware Pseudo-Label Selection for Semi-Supervised Text Recognition WACV 2023 Sharp Calibrated Gaussian Processes NeurIPS 2023 Should We Learn Most Likely Functions or Parameters? NeurIPS 2023 Simple and Efficient Confidence Score for Grading Whole Slide Images MIDL 2023 Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems AISTATS 2023 Single Image Depth Prediction Made Better: A Multivariate Gaussian Take CVPR 2023 SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals AISTATS 2023 SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process ICML 2023 Sparse Bayesian optimization AISTATS 2023 Sparse Graph Learning from Spatiotemporal Time Series JMLR 2023 Sparse Spectral Bayesian Permanental Process with Generalized Kernel AISTATS 2023 SPEECH: Structured Prediction with Energy-Based Event-Centric Hyperspheres ACL 2023 Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes ICML 2023 State and parameter learning with PARIS particle Gibbs ICML 2023 Statistical Foundations of Prior-Data Fitted Networks ICML 2023 Stein Π-Importance Sampling NeurIPS 2023