probabilistic modeling

Learning Sum-Product Networks with Direct and Indirect Variable Interactions ICML 2014 Lifted MAP Inference for Markov Logic Networks AISTATS 2014 Mind the Nuisance: Gaussian Process Classification using Privileged Noise NeurIPS 2014 Model-Based Relational RL When Object Existence is Partially Observable ICML 2014 Multiview Shape and Reflectance from Natural Illumination CVPR 2014 On Sparse Gaussian Chain Graph Models NeurIPS 2014 Parallel Sampling of HDPs using Sub-Cluster Splits NeurIPS 2014 Probabilistic low-rank matrix completion on finite alphabets NeurIPS 2014 Probably Approximately Correct MDP Learning and Control With Temporal Logic Constraints RSS 2014 Restricted Boltzmann machines modeling human choice NeurIPS 2014 Sparse Factor Analysis for Learning and Content Analytics JMLR 2014 Spatio-temporal Representations of Uncertainty in Spiking Neural Networks NeurIPS 2014 Spectral Methods for Indian Buffet Process Inference NeurIPS 2014 Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing NeurIPS 2014 Structure learning of antiferromagnetic Ising models NeurIPS 2014 A Lazy Man's Approach to Benchmarking: Semisupervised Classifier Evaluation and Recalibration CVPR 2013 A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks NeurIPS 2013 A Unified Probabilistic Approach Modeling Relationships between Attributes and Objects ICCV 2013 Bayesian inference for low rank spatiotemporal neural receptive fields NeurIPS 2013 Classifying With Confidence From Incomplete Information JMLR 2013 Computing the M Most Probable Modes of a Graphical Model AISTATS 2013 Dictionary Learning from Ambiguously Labeled Data CVPR 2013 Discovering Hidden Variables in Noisy-Or Networks using Quartet Tests NeurIPS 2013 Dynamic Copula Networks for Modeling Real-valued Time Series AISTATS 2013 Illuminant Chromaticity from Image Sequences ICCV 2013