model uncertainty

MOPO: Model-based Offline Policy Optimization NeurIPS 2020 Multi-Hypothesis Machine Translation Evaluation ACL 2020 Planning and Execution using Inaccurate Models with Provable Guarantees RSS 2020 Reinforcement Learning for Safety-Critical Control under Model Uncertainty, using Control Lyapunov Functions and Control Barrier Functions RSS 2020 Robust Multi-Agent Reinforcement Learning with Model Uncertainty NeurIPS 2020 Uncertainty Modeling for Machine Comprehension Systems using Efficient Bayesian Neural Networks COLING 2020 Accurate Layerwise Interpretable Competence Estimation NeurIPS 2019 Accurate Uncertainty Estimation and Decomposition in Ensemble Learning NeurIPS 2019 AdaNSP: Uncertainty-driven Adaptive Decoding in Neural Semantic Parsing ACL 2019 Bayesian Policy Optimization for Model Uncertainty ICLR 2019 Communication-Efficient Stochastic Gradient MCMC for Neural Networks AAAI 2019 Neural Graph Evolution: Towards Efficient Automatic Robot Design ICLR 2019 Practical Obstacles to Deploying Active Learning EMNLP 2019 Quantifying Uncertainties in Natural Language Processing Tasks AAAI 2019 Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control NeurIPS 2019 Universal Adversarial Perturbation via Prior Driven Uncertainty Approximation ICCV 2019 Bayesian Uncertainty Estimation for Batch Normalized Deep Networks ICML 2018 Gaussian Process Neural Networks for Speech Recognition Interspeech 2018 High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach ICML 2018 Predictive Uncertainty Estimation via Prior Networks NeurIPS 2018 Deep Bayesian Active Learning with Image Data ICML 2017 Determinantal Regularization for Ensemble Variable Selection AISTATS 2016 Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning ICML 2016 Robust Trajectory Optimization Under Frictional Contact with Iterative Learning RSS 2015 Bayes-Adaptive Simulation-based Search with Value Function Approximation NeurIPS 2014