Bayesian Inference

Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification ICML 2020 Neural Mixed Counting Models for Dispersed Topic Discovery ACL 2020 Neural Tangents: Fast and Easy Infinite Neural Networks in Python ICLR 2020 Neuronal Gaussian Process Regression NeurIPS 2020 Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization AISTATS 2020 Non-convex Learning via Replica Exchange Stochastic Gradient MCMC ICML 2020 Non-exchangeable feature allocation models with sublinear growth of the feature sizes AISTATS 2020 Nonmyopic Gaussian Process Optimization with Macro-Actions AISTATS 2020 Non-Parametric Calibration for Classification AISTATS 2020 Nonparametric Object and Parts Modeling With Lie Group Dynamics CVPR 2020 Non-Topical Coherence in Social Talk: A Call for Dialogue Model Enrichment ACL 2020 Not All Claims are Created Equal: Choosing the Right Statistical Approach to Assess Hypotheses ACL 2020 OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation UAI 2020 On Application of Bayesian Parametric and Non-parametric Methods for User Cohorting in Product Search ACL 2020 On Approximate Thompson Sampling with Langevin Algorithms ICML 2020 On casting importance weighted autoencoder to an EM algorithm to learn deep generative models AISTATS 2020 On Contrastive Learning for Likelihood-free Inference ICML 2020 On Importance Sampling-Based Evaluation of Latent Language Models ACL 2020 Online Bayesian Moment Matching based SAT Solver Heuristics ICML 2020 Online Neural Connectivity Estimation with Noisy Group Testing NeurIPS 2020 On Pruning for Score-Based Bayesian Network Structure Learning AISTATS 2020 On Semi-parametric Inference for BART ICML 2020 On the consistency of graph-based Bayesian semi-supervised learning and the scalability of sampling algorithms JMLR 2020 On the Expressiveness of Approximate Inference in Bayesian Neural Networks NeurIPS 2020 On Thompson Sampling for Smoother-than-Lipschitz Bandits AISTATS 2020