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Bayesian Inference

4821 directly classified papers

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Papers

On Kernelized Multi-armed Bandits ICML 2017
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings ACML 2017
Averaged Collapsed Variational Bayes Inference JMLR 2017
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms AISTATS 2017
Asymptotically exact inference in differentiable generative models AISTATS 2017
Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness AISTATS 2017
Noise-Blind Image Deblurring CVPR 2017
Improving Variational Methods via Pairwise Linear Response Identities JMLR 2017
Roles and Success in Wikipedia Talk Pages: Identifying Latent Patterns of Behavior IJCNLP 2017
Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets AISTATS 2017
Distributed Batch Gaussian Process Optimization ICML 2017
Stochastic Gradient Descent as Approximate Bayesian Inference JMLR 2017
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks NIPS 2017
Neural Variational Inference and Learning in Undirected Graphical Models NIPS 2017
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes NIPS 2017
Reducing Reparameterization Gradient Variance NIPS 2017
Variational Inference via $\chi$ Upper Bound Minimization NIPS 2017
Ensemble Sampling NIPS 2017
Hierarchical Implicit Models and Likelihood-Free Variational Inference NIPS 2017
Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models NIPS 2017
Doubly Stochastic Variational Inference for Deep Gaussian Processes NIPS 2017
Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models NIPS 2017
Fast Black-box Variational Inference through Stochastic Trust-Region Optimization NIPS 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles NIPS 2017
AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms NIPS 2017