Probabilistic Modeling

Polytope samplers for inference in ill-posed inverse problems 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 Producing Power-Law Distributions and Damping Word Frequencies with Two-Stage Language Models JMLR 2011 Query-Aware MCMC NeurIPS 2011 Robust Multi-Class Gaussian Process Classification NeurIPS 2011 Selective Prediction of Financial Trends with Hidden Markov Models NeurIPS 2011 Solving Decision Problems with Limited Information NeurIPS 2011 Spectral Methods for Learning Multivariate Latent Tree Structure NeurIPS 2011 Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning NeurIPS 2011 Structural equations and divisive normalization for energy-dependent component analysis NeurIPS 2011 t-divergence Based Approximate Inference NeurIPS 2011 Unifying Non-Maximum Likelihood Learning Objectives with Minimum KL Contraction NeurIPS 2011 Uniqueness of Belief Propagation on Signed Graphs NeurIPS 2011 Variational Gaussian Process Dynamical Systems NeurIPS 2011 Accounting for network effects in neuronal responses using L1 regularized point process models NeurIPS 2010 A Log-Domain Implementation of the Diffusion Network in Very Large Scale Integration NeurIPS 2010 A Markov-Chain Monte Carlo Approach to Simultaneous Localization and Mapping AISTATS 2010 An EM Algorithm on BDDs with Order Encoding for Logic-based Probabilistic Models ACML 2010 A New Probabilistic Model for Rank Aggregation NeurIPS 2010 A POMDP Extension with Belief-dependent Rewards NeurIPS 2010 Approximate Inference by Compilation to Arithmetic Circuits NeurIPS 2010 Approximate inference in continuous time Gaussian-Jump processes NeurIPS 2010