variational inference

On the Calibration and Uncertainty with Pólya-Gamma Augmentation for Dialog Retrieval Models AAAI 2023 On the Statistical Consistency of Risk-Sensitive Bayesian Decision-Making NeurIPS 2023 Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach AISTATS 2023 PAC-Bayesian Generalization Bounds for Adversarial Generative Models ICML 2023 Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model NeurIPS 2023 Partial Multi-Label Learning with Probabilistic Graphical Disambiguation NeurIPS 2023 Particle-based Variational Inference with Generalized Wasserstein Gradient Flow NeurIPS 2023 Particle-based Variational Inference with Preconditioned Functional Gradient Flow ICLR 2023 Perceptual Improvement of Deep Neural Network (DNN) Speech Coder Using Parametric and Non-parametric Density Models Interspeech 2023 {PF}$^2$ES: Parallel Feasible Pareto Frontier Entropy Search for Multi-Objective Bayesian Optimization AISTATS 2023 Piecewise Deterministic Markov Processes for Bayesian Neural Networks UAI 2023 Plausible Uncertainties for Human Pose Regression ICCV 2023 Pluralistic Aging Diffusion Autoencoder ICCV 2023 Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior NeurIPS 2023 Positive Distribution Pollution: Rethinking Positive Unlabeled Learning from a Unified Perspective AAAI 2023 POV-SLAM: Probabilistic Object-Aware Variational SLAM in Semi-Static Environments RSS 2023 Probabilistic Attention-to-Influence Neural Models for Event Sequences ICML 2023 Probabilistic Imputation for Time-series Classification with Missing Data ICML 2023 Probabilistic Integration of Object Level Annotations in Chest X-Ray Classification WACV 2023 Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation ICCV 2023 Probabilistic Transformer: A Probabilistic Dependency Model for Contextual Word Representation ACL 2023 Probabilistic Weight Fixing: Large-scale training of neural network weight uncertainties for quantisation. NeurIPS 2023 Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond NeurIPS 2023 Provable convergence guarantees for black-box variational inference NeurIPS 2023 Provable Multi-instance Deep AUC Maximization with Stochastic Pooling ICML 2023