Bayesian & Probabilistic

VaB-AL: Incorporating Class Imbalance and Difficulty With Variational Bayes for Active Learning CVPR 2021 Value-at-Risk Optimization with Gaussian Processes ICML 2021 Variational Auto-Regressive Gaussian Processes for Continual Learning ICML 2021 variational combinatorial sequential monte carlo methods for bayesian phylogenetic inference UAI 2021 Variational inference for nonlinear ordinary differential equations AISTATS 2021 Variational Information Bottleneck for Effective Low-Resource Fine-Tuning ICLR 2021 Variational Intrinsic Control Revisited ICLR 2021 Variational Multi-Task Learning with Gumbel-Softmax Priors NeurIPS 2021 Variational Pedestrian Detection CVPR 2021 Variational Weakly Supervised Sentiment Analysis with Posterior Regularization EACL 2021 VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning JMLR 2021 Vector Quantized Bayesian Neural Network Inference for Data Streams AAAI 2021 VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media NeurIPS 2021 VLGrammar: Grounded Grammar Induction of Vision and Language ICCV 2021 VMLoc: Variational Fusion For Learning-Based Multimodal Camera Localization AAAI 2021 Weighted model counting with conditional weights for Bayesian networks UAI 2021 Weighted model estimation for offline model-based reinforcement learning NeurIPS 2021 What Are Bayesian Neural Network Posteriors Really Like? ICML 2021 When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting NeurIPS 2021 When OT meets MoM: Robust estimation of Wasserstein Distance AISTATS 2021 When random initializations help: a study of variational inference for community detection JMLR 2021 A Bayesian Nonparametrics View into Deep Representations NeurIPS 2020 A Complete Characterization of Projectivity for Statistical Relational Models IJCAI 2020 Adaptive Discretization for Evaluation of Probabilistic Cost Functions AISTATS 2020 Adaptive Sampling for Stochastic Risk-Averse Learning NeurIPS 2020