uncertainty quantification

Uncertainty Quantification and Deep Ensembles NeurIPS 2021 Uncertainty Quantification in CNN Through the Bootstrap of Convex Neural Networks AAAI 2021 Uncertainty quantification using martingales for misspecified Gaussian processes ALT 2021 Uncertainty Reduction for Model Adaptation in Semantic Segmentation CVPR 2021 Uncertainty Sets for Image Classifiers using Conformal Prediction ICLR 2021 Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning ICML 2021 Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon AISTATS 2021 Vector Quantized Bayesian Neural Network Inference for Data Streams AAAI 2021 V-statistics and Variance Estimation JMLR 2021 Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data ICML 2021 When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting NeurIPS 2021 Whittle Networks: A Deep Likelihood Model for Time Series ICML 2021 3D semi-supervised learning with uncertainty-aware multi-view co-training WACV 2020 Actively Learning Gaussian Process Dynamics L4DC 2020 AdaTune: Adaptive Tensor Program Compilation Made Efficient NeurIPS 2020 Aggregation of Perspectives Using the Constellations Approach to Probabilistic Argumentation AAAI 2020 A Heteroscedastic Uncertainty Model for Decoupling Sources of MRI Image Quality MIDL 2020 BaKer-Nets: Bayesian Random Kernel Mapping Networks IJCAI 2020 Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation UAI 2020 Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues AAAI 2020 Bayesian Deep Ensembles via the Neural Tangent Kernel NeurIPS 2020 Bayesian Graph Neural Networks with Adaptive Connection Sampling ICML 2020 Bayesian Image Classification with Deep Convolutional Gaussian Processes AISTATS 2020 Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels NeurIPS 2020 Being Bayesian about Categorical Probability ICML 2020