Bayesian Learning

Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks NeurIPS 2017 Differential Privacy for Bayesian Inference through Posterior Sampling JMLR 2017 Discovering Relevance-Dependent Bicluster Structure from Relational Data IJCAI 2017 Discriminative Bayesian Nonparametric Clustering IJCAI 2017 Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling IJCAI 2017 Evaluating Bayesian Models with Posterior Dispersion Indices ICML 2017 Fast amortized inference of neural activity from calcium imaging data with variational autoencoders NeurIPS 2017 Flexible statistical inference for mechanistic models of neural dynamics NeurIPS 2017 Gauging Variational Inference NeurIPS 2017 Gray-box Inference for Structured Gaussian Process Models AISTATS 2017 Information-theoretic limits of Bayesian network structure learning AISTATS 2017 Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo ICML 2017 Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes NeurIPS 2017 Learning Nonparametric Forest Graphical Models with Prior Information AISTATS 2017 Learning Structured Weight Uncertainty in Bayesian Neural Networks AISTATS 2017 Linearly constrained Gaussian processes NeurIPS 2017 Locally Consistent Bayesian Network Scores for Multi-Relational Data IJCAI 2017 Local-to-Global Bayesian Network Structure Learning ICML 2017 Model evidence from nonequilibrium simulations NeurIPS 2017 Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons NeurIPS 2017 Nonparametric Online Machine Learning with Kernels IJCAI 2017 On the Hyperprior Choice for the Global Shrinkage Parameter in the Horseshoe Prior AISTATS 2017 Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models JMLR 2017 Personalizing Gesture Recognition Using Hierarchical Bayesian Neural Networks CVPR 2017 Post-Inference Prior Swapping ICML 2017