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Bayesian Inference

4821 directly classified papers

Papers per year

Papers

Variational Dropout Sparsifies Deep Neural Networks ICML 2017
Variational Boosting: Iteratively Refining Posterior Approximations ICML 2017
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks ICML 2017
Differentially private Bayesian learning on distributed data NIPS 2017
Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit NIPS 2017
Constrained Bayesian Reinforcement Learning via Approximate Linear Programming IJCAI 2017
Factorized Asymptotic Bayesian Policy Search for POMDPs IJCAI 2017
On Thompson Sampling and Asymptotic Optimality IJCAI 2017
Tensor Decomposition with Missing Indices IJCAI 2017
Linearly constrained Gaussian processes NIPS 2017
Renyi Differential Privacy Mechanisms for Posterior Sampling NIPS 2017
Bayesian Optimization with Tree-structured Dependencies ICML 2017
A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent NIPS 2017
From Patches to Images: A Nonparametric Generative Model ICML 2017
Evaluating Bayesian Models with Posterior Dispersion Indices ICML 2017
Detecting Dependencies in Sparse, Multivariate Databases Using Probabilistic Programming and Non-parametric Bayes AISTATS 2017
Multiresolution Kernel Approximation for Gaussian Process Regression NIPS 2017
Neural Graphical Models over Strings for Principal Parts Morphological Paradigm Completion EACL 2017
A causal framework for explaining the predictions of black-box sequence-to-sequence models EMNLP 2017
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation ICML 2017
Subband Selection for Binaural Speech Source Localization INTERSPEECH 2017
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search NIPS 2017
Adaptive Bayesian Sampling with Monte Carlo EM NIPS 2017
Dropout Inference in Bayesian Neural Networks with Alpha-divergences ICML 2017
Scalable Levy Process Priors for Spectral Kernel Learning NIPS 2017