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Bayesian Inference

5,566 papers

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Papers

Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era AISTATS 2019
On Theory for BART AISTATS 2019
Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models AISTATS 2019
Binary Space Partitioning Forest AISTATS 2019
A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes AISTATS 2019
Database Alignment with Gaussian Features AISTATS 2019
Reparameterizing Distributions on Lie Groups AISTATS 2019
Harmonizable mixture kernels with variational Fourier features AISTATS 2019
Multiscale Gaussian Process Level Set Estimation AISTATS 2019
Efficient Bayes Risk Estimation for Cost-Sensitive Classification AISTATS 2019
Interpreting Black Box Predictions using Fisher Kernels AISTATS 2019
ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery AISTATS 2019
Adaptive Minimax Regret against Smooth Logarithmic Losses over High-Dimensional l1-Balls via Envelope Complexity AISTATS 2019
Ising Models with Latent Conditional Gaussian Variables ALT 2019
Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret COLT 2019
Nonconvex sampling with the Metropolis-adjusted Langevin algorithm COLT 2019
Striking the Right Balance With Uncertainty CVPR 2019
Reducing Uncertainty in Undersampled MRI Reconstruction With Active Acquisition CVPR 2019
Variational Convolutional Neural Network Pruning CVPR 2019
DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs CVPR 2019
Semantic Alignment: Finding Semantically Consistent Ground-Truth for Facial Landmark Detection CVPR 2019
What's to Know? Uncertainty as a Guide to Asking Goal-Oriented Questions CVPR 2019
Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach CVPR 2019
A Bayesian Perspective on the Deep Image Prior CVPR 2019
Enhanced Bayesian Compression via Deep Reinforcement Learning CVPR 2019