Bayesian Inference

Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm COLT 2021 Optimal Order Simple Regret for Gaussian Process Bandits NeurIPS 2021 Optimized auxiliary particle filters: adapting mixture proposals via convex optimization UAI 2021 Optimizing Conditional Value-At-Risk of Black-Box Functions NeurIPS 2021 Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD NeurIPS 2021 Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation ICML 2021 Outcome-Driven Reinforcement Learning via Variational Inference NeurIPS 2021 Out of a Hundred Trials, How Many Errors Does Your Speaker Verifier Make? Interspeech 2021 PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes COLT 2021 PAC Confidence Predictions for Deep Neural Network Classifiers ICLR 2021 PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees ICML 2021 PALM: Probabilistic area loss Minimization for Protein Sequence Alignment UAI 2021 Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement NeurIPS 2021 Parallel tempering on optimized paths ICML 2021 Particle-Gibbs Sampling for Bayesian Feature Allocation Models JMLR 2021 Partition Function Estimation: A Quantitative Study IJCAI 2021 PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming AISTATS 2021 Periodic Activation Functions Induce Stationarity NeurIPS 2021 Persuading Voters in District-based Elections AAAI 2021 Physics-aware, probabilistic model order reduction with guaranteed stability ICLR 2021 Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks ICML 2021 Posterior Differential Regularization with f-divergence for Improving Model Robustness NAACL 2021 Posterior Meta-Replay for Continual Learning NeurIPS 2021 Post-hoc loss-calibration for Bayesian neural networks UAI 2021 Post-Hoc Uncertainty Calibration for Domain Drift Scenarios CVPR 2021