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Bayesian Inference

1724 directly classified papers

Papers per year

Papers

Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression AAAI 2020
Fragmentation Coagulation Based Mixed Membership Stochastic Blockmodel AAAI 2020
Radial and Directional Posteriors for Bayesian Deep Learning AAAI 2020
Particle Filter Recurrent Neural Networks AAAI 2020
OpenMarkov, an Open-Source Tool for Probabilistic Graphical Models IJCAI 2019
Communication-Efficient Stochastic Gradient MCMC for Neural Networks AAAI 2019
Word Familiarity Rate Estimation Using a Bayesian Linear Mixed Model EMNLP 2019
The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration IJCAI 2019
A Bayesian Approach for Sequence Tagging with Crowds EMNLP 2019
Neural RGB(r)D Sensing: Depth and Uncertainty From a Video Camera CVPR 2019
Dichromatic Model Based Temporal Color Constancy for AC Light Sources CVPR 2019
What's to Know? Uncertainty as a Guide to Asking Goal-Oriented Questions CVPR 2019
A Bayesian Perspective on the Deep Image Prior CVPR 2019
Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning ICML 2019
Automatic Posterior Transformation for Likelihood-Free Inference ICML 2019
Variational Inference MPC for Bayesian Model-based Reinforcement Learning CORL 2019
Differentially Private Bayesian Linear Regression NIPS 2019
Embarrassingly Parallel MCMC using Deep Invertible Transformations UAI 2019
Subspace Inference for Bayesian Deep Learning UAI 2019
Generating and Sampling Orbits for Lifted Probabilistic Inference UAI 2019
Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters NIPS 2019
Computational Separations between Sampling and Optimization NIPS 2019
Noise Contrastive Priors for Functional Uncertainty UAI 2019
Variational Training for Large-Scale Noisy-OR Bayesian Networks UAI 2019
Probabilistic Programming for Birth-Death Models of Evolution Using an Alive Particle Filter with Delayed Sampling UAI 2019