Probability

Hamiltonian Monte Carlo Without Detailed Balance ICML 2014 Hamming Ball Auxiliary Sampling for Factorial Hidden Markov Models NeurIPS 2014 Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data ICML 2014 Learning Graphs with a Few Hubs ICML 2014 Learning without concentration COLT 2014 Linear and Parallel Learning of Markov Random Fields ICML 2014 Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians ICML 2014 Memory (and Time) Efficient Sequential Monte Carlo ICML 2014 Modeling Correlated Arrival Events with Latent Semi-Markov Processes ICML 2014 On Sparse Gaussian Chain Graph Models NeurIPS 2014 PEWA: Patch-based Exponentially Weighted Aggregation for image denoising NeurIPS 2014 Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics AISTATS 2014 Projecting Markov Random Field Parameters for Fast Mixing NeurIPS 2014 Randomized Experimental Design for Causal Graph Discovery NeurIPS 2014 Rectangular Tiling Process ICML 2014 Spherical Hamiltonian Monte Carlo for Constrained Target Distributions ICML 2014 The More, the Merrier: the Blessing of Dimensionality for Learning Large Gaussian Mixtures COLT 2014 Analyzing Hogwild Parallel Gaussian Gibbs Sampling NeurIPS 2013 Annealing between distributions by averaging moments NeurIPS 2013 Approximate Gaussian process inference for the drift function in stochastic differential equations NeurIPS 2013 A simple sketching algorithm for entropy estimation over streaming data AISTATS 2013 Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions NeurIPS 2013 Bayesian entropy estimation for binary spike train data using parametric prior knowledge NeurIPS 2013 Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC NeurIPS 2013 Blind Signal Separation in the Presence of Gaussian Noise COLT 2013