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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

Learning Big Gaussian Bayesian Networks: Partition, Estimation and Fusion JMLR 2020
Latent Simplex Position Model: High Dimensional Multi-view Clustering with Uncertainty Quantification JMLR 2020
Expectation Propagation as a Way of Life: A Framework for Bayesian Inference on Partitioned Data JMLR 2020
BINOCULARS for efficient, nonmyopic sequential experimental design ICML 2020
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences ICML 2020
Information Particle Filter Tree: An Online Algorithm for POMDPs with Belief-Based Rewards on Continuous Domains ICML 2020
Learning Bayesian Networks Under Sparsity Constraints: A Parameterized Complexity Analysis IJCAI 2020
Reconsidering Generative Objectives For Counterfactual Reasoning NIPS 2020
Bayesian Case-Exclusion and Personalized Explanations for Sustainable Dairy Farming (Extended Abstract) IJCAI 2020
Pitfalls of Learning a Reward Function Online IJCAI 2020
Towards Interpretable Clinical Diagnosis with Bayesian Network Ensembles Stacked on Entity-Aware CNNs ACL 2020
Baxter Permutation Process NIPS 2020
Learning in the Wild with Incremental Skeptical Gaussian Processes IJCAI 2020
An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles IJCAI 2020
Bayesian Hierarchical Words Representation Learning ACL 2020
Uncertainty Modeling for Machine Comprehension Systems using Efficient Bayesian Neural Networks COLING 2020
The impact of preprint servers in the formation of novel ideas EMNLP 2020
Mitigating Gender Bias Amplification in Distribution by Posterior Regularization ACL 2020
Quantile Propagation for Wasserstein-Approximate Gaussian Processes NIPS 2020
Projected Stein Variational Gradient Descent NIPS 2020
Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters NIPS 2020
Learnable Bernoulli Dropout for Bayesian Deep Learning AISTATS 2020
Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning AISTATS 2020
Bayesian Multi-type Mean Field Multi-agent Imitation Learning NIPS 2020
Theory-Based Causal Transfer:Integrating Instance-Level Induction and Abstract-Level Structure Learning AAAI 2020