Bayesian Inference

Thompson Sampling with Information Relaxation Penalties NeurIPS 2019 Topic-Guided Variational Auto-Encoder for Text Generation NAACL 2019 Towards Efficient Detection and Optimal Response against Sophisticated Opponents IJCAI 2019 Tracking Discrete and Continuous Entity State for Process Understanding NAACL 2019 Traffic Updates: Saying a Lot While Revealing a Little AAAI 2019 Training Variational Autoencoders with Buffered Stochastic Variational Inference AISTATS 2019 Trust Dynamics and Transfer across Human-Robot Interaction Tasks: Bayesian and Neural Computational Models IJCAI 2019 Trust Region Sequential Variational Inference ACML 2019 Unbiased Implicit Variational Inference AISTATS 2019 Unbiased Smoothing using Particle Independent Metropolis-Hastings AISTATS 2019 Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference ICCV 2019 Uncertainty-based Continual Learning with Adaptive Regularization NeurIPS 2019 Uncertainty on Asynchronous Time Event Prediction NeurIPS 2019 Uncover the Ground-Truth Relations in Distant Supervision: A Neural Expectation-Maximization Framework EMNLP 2019 Understanding and Accelerating Particle-Based Variational Inference ICML 2019 Understanding MCMC Dynamics as Flows on the Wasserstein Space ICML 2019 Universal Boosting Variational Inference NeurIPS 2019 Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach CVPR 2019 Using Contextual Information to Improve Blood Glucose Prediction MLHC 2019 Using Simulation to Improve Sample-Efficiency of Bayesian Optimization for Bipedal Robots JMLR 2019 VAE-Based Regularization for Deep Speaker Embedding Interspeech 2019 Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution AISTATS 2019 Variational Annealing of GANs: A Langevin Perspective ICML 2019 Variational Autoencoder with Implicit Optimal Priors AAAI 2019 Variational Bayesian Decision-making for Continuous Utilities NeurIPS 2019