Bayesian Learning

Mixed variable Bayesian optimization with frequency modulated kernels UAI 2021 Model-based Reinforcement Learning for Continuous Control with Posterior Sampling ICML 2021 Modeling Sense Structure in Word Usage Graphs with the Weighted Stochastic Block Model ACL 2021 Modular Gaussian Processes for Transfer Learning NeurIPS 2021 MOTS: Minimax Optimal Thompson Sampling ICML 2021 MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning ICML 2021 Near-Optimal Data Source Selection for Bayesian Learning L4DC 2021 Neural Thompson Sampling ICLR 2021 Nonparametric Decomposition of Sparse Tensors ICML 2021 No-Regret Algorithms for Private Gaussian Process Bandit Optimization AISTATS 2021 On Information Gain and Regret Bounds in Gaussian Process Bandits AISTATS 2021 On the Parameterized Complexity of Polytree Learning IJCAI 2021 Optimal Thompson Sampling strategies for support-aware CVaR bandits ICML 2021 Overcoming Catastrophic Forgetting by Bayesian Generative Regularization ICML 2021 Periodic Activation Functions Induce Stationarity NeurIPS 2021 PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception AAAI 2021 Policy Gradient Bayesian Robust Optimization for Imitation Learning ICML 2021 Posterior Meta-Replay for Continual Learning NeurIPS 2021 Precise characterization of the prior predictive distribution of deep ReLU networks NeurIPS 2021 Predictive Complexity Priors AISTATS 2021 Probabilistic Iterative Methods for Linear Systems JMLR 2021 Probability Paths and the Structure of Predictions over Time NeurIPS 2021 Quantifying Contextual Aspects of Inter-annotator Agreement in Intertextuality Research EMNLP 2021 Rao-Blackwellised parallel MCMC AISTATS 2021 Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning ICML 2021