Bayesian Inference

MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models UAI 2020 Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula NeurIPS 2020 Matrix Inference and Estimation in Multi-Layer Models NeurIPS 2020 Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles AAAI 2020 Meta-Consolidation for Continual Learning NeurIPS 2020 Meta-Learning PAC-Bayes Priors in Model Averaging AAAI 2020 Minimum Bayes Risk Training of RNN-Transducer for End-to-End Speech Recognition Interspeech 2020 Mixed Hamiltonian Monte Carlo for Mixed Discrete and Continuous Variables NeurIPS 2020 Mixed-Variable Bayesian Optimization IJCAI 2020 Model-Based Diagnosis with Uncertain Observations AAAI 2020 Model-based reinforcement learning for biological sequence design ICLR 2020 Model Fusion with Kullback-Leibler Divergence ICML 2020 Model Selection for Production System via Automated Online Experiments NeurIPS 2020 Modular Meta-Learning with Shrinkage NeurIPS 2020 MRFMap: Online Probabilistic 3D Mapping using Forward Ray Sensor Models RSS 2020 Multi-attribute Bayesian optimization with interactive preference learning AISTATS 2020 Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning NeurIPS 2020 Multi-Fidelity Bayesian Optimization via Deep Neural Networks NeurIPS 2020 Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization ICML 2020 Multi-Fidelity Black-Box Optimization for Time-Optimal Quadrotor Maneuvers RSS 2020 Multi-Fidelity Multi-Objective Bayesian Optimization: An Output Space Entropy Search Approach AAAI 2020 Multiplicative Gaussian Particle Filter AISTATS 2020 Multi-task Causal Learning with Gaussian Processes NeurIPS 2020 NeoNav: Improving the Generalization of Visual Navigation via Generating Next Expected Observations AAAI 2020 Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems NeurIPS 2020