Bayesian Learning

Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes ICLR 2021 Bayesian Latent Factor Model for Higher-order Data ACML 2021 Bayesian Model-Agnostic Meta-Learning with Matrix-Valued Kernels for Quality Estimation ACL 2021 Bayesian Model Averaging for Causality Estimation and its Approximation based on Gaussian Scale Mixture Distributions AISTATS 2021 Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression CVPR 2021 Bayesian neural network unit priors and generalized Weibull-tail property ACML 2021 Bayesian Nonparametric Space Partitions: A Survey IJCAI 2021 Bayesian streaming sparse Tucker decomposition UAI 2021 Bayesian Structural Adaptation for Continual Learning ICML 2021 Bayesian Text Classification and Summarization via A Class-Specified Topic Model JMLR 2021 Bayesian Topic Regression for Causal Inference EMNLP 2021 Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example AAAI 2021 Black-box density function estimation using recursive partitioning ICML 2021 Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data NeurIPS 2021 Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems AAAI 2021 Collaborative Bayesian Optimization with Fair Regret ICML 2021 Comparing Symbolic Models of Language via Bayesian Inference (Student Abstract) AAAI 2021 Consistency of Gaussian Process Regression in Metric Spaces JMLR 2021 Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors AISTATS 2021 Contraction L1-Adaptive Control using Gaussian Processes L4DC 2021 Cost-aware Graph Generation: A Deep Bayesian Optimization Approach AAAI 2021 Dangers of Bayesian Model Averaging under Covariate Shift NeurIPS 2021 Deconditional Downscaling with Gaussian Processes NeurIPS 2021 Deep kernel processes ICML 2021 Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect NeurIPS 2021