Bayesian Inference

An Alternative Probabilistic Interpretation of the Huber Loss CVPR 2021 Analysing the Noise Model Error for Realistic Noisy Label Data AAAI 2021 Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler JMLR 2021 Analyzing the Generalization Capability of SGLD Using Properties of Gaussian Channels NeurIPS 2021 Anchor-Constrained Viterbi for Set-Supervised Action Segmentation CVPR 2021 An Empirical Study of Bayesian Optimization: Acquisition Versus Partition JMLR 2021 A New Representation of Successor Features for Transfer across Dissimilar Environments ICML 2021 Animal pose estimation from video data with a hierarchical von Mises-Fisher-Gaussian model AISTATS 2021 An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence NeurIPS 2021 An Information-Theoretic Framework for Unifying Active Learning Problems AAAI 2021 An MRF-UNet Product of Experts for Image Segmentation MIDL 2021 A Nonmyopic Approach to Cost-Constrained Bayesian Optimization UAI 2021 An Overview of Uncertainty Calibration for Text Classification and the Role of Distillation ACL 2021 Antipodes of Label Differential Privacy: PATE and ALIBI NeurIPS 2021 A PAC-Bayes Analysis of Adversarial Robustness NeurIPS 2021 A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks ICLR 2021 Approximate Bayesian Computation for an Explicit-Duration Hidden Markov Model of COVID-19 Hospital Trajectories MLHC 2021 A Probabilistic Approach to Neural Network Pruning ICML 2021 A Probabilistic State Space Model for Joint Inference from Differential Equations and Data NeurIPS 2021 Are We Forgetting about Compositional Optimisers in Bayesian Optimisation? JMLR 2021 A sampling-based circuit for optimal decision making NeurIPS 2021 A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models AISTATS 2021 A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs NeurIPS 2021 A statistical perspective on distillation ICML 2021 A statistical theory of cold posteriors in deep neural networks ICLR 2021