Bayesian & Probabilistic

Bayesian Attention Modules NeurIPS 2020 Bayesian Bits: Unifying Quantization and Pruning NeurIPS 2020 Bayesian Case-Exclusion and Personalized Explanations for Sustainable Dairy Farming (Extended Abstract) IJCAI 2020 Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks NeurIPS 2020 Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation ICML 2020 Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods NeurIPS 2020 Bayesian Graph Neural Networks with Adaptive Connection Sampling ICML 2020 Bayesian Hierarchical Words Representation Learning ACL 2020 Bayesian Image Classification with Deep Convolutional Gaussian Processes AISTATS 2020 Bayesian joint state and parameter tracking in autoregressive models L4DC 2020 Bayesian Learning of Probabilistic Dipole Inversion for Quantitative Susceptibility Mapping MIDL 2020 Bayesian Learning with Adaptive Load Allocation Strategies L4DC 2020 Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels NeurIPS 2020 Bayesian Meta Sampling for Fast Uncertainty Adaptation ICLR 2020 Bayesian Methods for Semi-supervised Text Annotation COLING 2020 Bayesian Multi-type Mean Field Multi-agent Imitation Learning NeurIPS 2020 Bayesian network structure learning with causal effects in the presence of latent variables PGM 2020 Bayesian Online Prediction of Change Points UAI 2020 Bayesian Optimisation for Premise Selection in Automated Theorem Proving (Student Abstract) AAAI 2020 Bayesian Optimization of Risk Measures NeurIPS 2020 Bayesian Reinforcement Learning via Deep, Sparse Sampling AISTATS 2020 Bayesian Robust Optimization for Imitation Learning NeurIPS 2020 Bayesian Sparsification of Deep C-valued Networks ICML 2020 BayesRace: Learning to race autonomously using prior experience CoRL 2020 BayesSuites: An Open Web Framework for Visualization of Massive Bayesian Networks PGM 2020