Bayesian & Probabilistic

Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes NeurIPS 2020 Temporal Logic Point Processes ICML 2020 Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk Estimation NeurIPS 2020 Text-Based Ideal Points ACL 2020 The Autoencoding Variational Autoencoder NeurIPS 2020 The Boomerang Sampler ICML 2020 The continuous categorical: a novel simplex-valued exponential family ICML 2020 The impact of preprint servers in the formation of novel ideas EMNLP 2020 The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks ICML 2020 Theory-Based Causal Transfer:Integrating Instance-Level Induction and Abstract-Level Structure Learning AAAI 2020 The Potts-Ising model for discrete multivariate data NeurIPS 2020 The Stanford Acuity Test: A Precise Vision Test Using Bayesian Techniques and a Discovery in Human Visual Response AAAI 2020 The Unreasonable Effectiveness of Inverse Reinforcement Learning in Advancing Cancer Research AAAI 2020 The Usual Suspects? Reassessing Blame for VAE Posterior Collapse ICML 2020 The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget ICLR 2020 Thompson Sampling for Unsupervised Sequential Selection ACML 2020 Topic Balancing with Additive Regularization of Topic Models ACL 2020 To Relieve Your Headache of Training an MRF, Take AdVIL ICLR 2020 Total Deep Variation for Linear Inverse Problems CVPR 2020 Towards a Hierarchical Bayesian Model of Multi-View Anomaly Detection IJCAI 2020 Towards Interpretable Clinical Diagnosis with Bayesian Network Ensembles Stacked on Entity-Aware CNNs ACL 2020 Towards neural networks that provably know when they don't know ICLR 2020 Towards Scalable Bayesian Learning of Causal DAGs NeurIPS 2020 Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization AAAI 2020 Tuning Causal Discovery Algorithms PGM 2020