Bayesian Inference

Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings NeurIPS 2015 Large-scale Distributed Dependent Nonparametric Trees ICML 2015 Latent Bayesian melding for integrating individual and population models NeurIPS 2015 Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data ICML 2015 Learning Bayesian Networks with Thousands of Variables NeurIPS 2015 Learning Deep Sigmoid Belief Networks with Data Augmentation AISTATS 2015 Learning From Massive Noisy Labeled Data for Image Classification CVPR 2015 Learning spatiotemporal trajectories from manifold-valued longitudinal data NeurIPS 2015 Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels NeurIPS 2015 Learning structured densities via infinite dimensional exponential families NeurIPS 2015 Learning The Structure of Deep Convolutional Networks ICCV 2015 Lifted Inference Rules With Constraints NeurIPS 2015 Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes NeurIPS 2015 Local Expectation Gradients for Black Box Variational Inference NeurIPS 2015 Low-Rank Tensor Approximation With Laplacian Scale Mixture Modeling for Multiframe Image Denoising ICCV 2015 MAP Disparity Estimation Using Hidden Markov Trees ICCV 2015 Markov Mixed Membership Models ICML 2015 Max-Margin Majority Voting for Learning from Crowds NeurIPS 2015 MCMC for Variationally Sparse Gaussian Processes NeurIPS 2015 Measuring Sample Quality with Stein's Method NeurIPS 2015 Multi-Conditional Latent Variable Model for Joint Facial Action Unit Detection ICCV 2015 Multi-Feature Max-Margin Hierarchical Bayesian Model for Action Recognition CVPR 2015 Nested Sequential Monte Carlo Methods ICML 2015 Neural Adaptive Sequential Monte Carlo NeurIPS 2015 Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood ICML 2015