Probabilistic Modeling

Mixed-Variate Restricted Boltzmann Machines ACML 2011 Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability NeurIPS 2011 Nonstandard Interpretations of Probabilistic Programs for Efficient Inference NeurIPS 2011 On Causal Discovery with Cyclic Additive Noise Models NeurIPS 2011 On Time Varying Undirected Graphs AISTATS 2011 On Tracking The Partition Function NeurIPS 2011 Optimal Reinforcement Learning for Gaussian Systems NeurIPS 2011 Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees AISTATS 2011 Probabilistic amplitude and frequency demodulation NeurIPS 2011 Probabilistic Analysis of Correctness of High-Level Robot Behavior with Sensor Error RSS 2011 Probabilistic Joint Image Segmentation and Labeling NeurIPS 2011 Probabilistic Modeling of Dependencies Among Visual Short-Term Memory Representations NeurIPS 2011 Quadratic Weighted Automata:Spectral Algorithm and Likelihood Maximization ACML 2011 Query-Aware MCMC NeurIPS 2011 Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance NeurIPS 2011 Robust Multi-Class Gaussian Process Classification NeurIPS 2011 Scalable Training of Mixture Models via Coresets NeurIPS 2011 Selective Prediction of Financial Trends with Hidden Markov Models NeurIPS 2011 Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation NeurIPS 2011 Spectral Methods for Learning Multivariate Latent Tree Structure NeurIPS 2011 Structural equations and divisive normalization for energy-dependent component analysis NeurIPS 2011 t-divergence Based Approximate Inference NeurIPS 2011 Testing a Bayesian Measure of Representativeness Using a Large Image Database NeurIPS 2011 The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling AISTATS 2011 The Doubly Correlated Nonparametric Topic Model NeurIPS 2011