uncertainty estimation

Multi-Task Time Series Analysis applied to Drug Response Modelling AISTATS 2019 Neural RGB(r)D Sensing: Depth and Uncertainty From a Video Camera CVPR 2019 Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams ICLR 2019 Prediction of Disease Progression in Multiple Sclerosis Patients using Deep Learning Analysis of MRI Data MIDL 2019 Probabilistic Face Embeddings ICCV 2019 Pushing the Frontiers of Unconstrained Crowd Counting: New Dataset and Benchmark Method ICCV 2019 Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces ICML 2019 Reparameterizing Distributions on Lie Groups AISTATS 2019 Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness NeurIPS 2019 Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging UAI 2019 Self-Supervised Mixture-of-Experts by Uncertainty Estimation AAAI 2019 The Functional Neural Process NeurIPS 2019 U-CAM: Visual Explanation Using Uncertainty Based Class Activation Maps ICCV 2019 Uncertainty Guided Multi-Scale Residual Learning-Using a Cycle Spinning CNN for Single Image De-Raining CVPR 2019 Using Pre-Training Can Improve Model Robustness and Uncertainty ICML 2019 Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty NeurIPS 2019 A Scalable Laplace Approximation for Neural Networks ICLR 2018 Bayesian Uncertainty Estimation for Batch Normalized Deep Networks ICML 2018 Covariances, Robustness, and Variational Bayes JMLR 2018 Interpreting Neural Networks with Nearest Neighbors EMNLP 2018 Lightweight Probabilistic Deep Networks CVPR 2018 Long-Term On-Board Prediction of People in Traffic Scenes Under Uncertainty CVPR 2018 Noisy Natural Gradient as Variational Inference ICML 2018 Randomized Prior Functions for Deep Reinforcement Learning NeurIPS 2018 Scalable approximate Bayesian inference for particle tracking data ICML 2018