Probabilistic Modeling

Stein Variational Gradient Descent as Gradient Flow NeurIPS 2017 SVD-Based Screening for the Graphical Lasso IJCAI 2017 Symbolic Priors for RNN-based Semantic Parsing IJCAI 2017 Targeting EEG/LFP Synchrony with Neural Nets NeurIPS 2017 Tensor Belief Propagation ICML 2017 Testing Bayesian Networks COLT 2017 The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities NeurIPS 2017 The Mixing of Markov Chains on Linear Extensions in Practice IJCAI 2017 Time-dependent spatially varying graphical models, with application to brain fMRI data analysis NeurIPS 2017 Unified Representation and Lifted Sampling for Generative Models of Social Networks IJCAI 2017 Universal Reinforcement Learning Algorithms: Survey and Experiments IJCAI 2017 Uprooting and Rerooting Higher-Order Graphical Models NeurIPS 2017 Using Graphs of Classifiers to Impose Declarative Constraints on Semi-supervised Learning IJCAI 2017 Variational Autoencoded Regression: High Dimensional Regression of Visual Data on Complex Manifold CVPR 2017 Weighted Model Integration with Orthogonal Transformations IJCAI 2017 Zero-Inflated Exponential Family Embeddings ICML 2017 Achieving budget-optimality with adaptive schemes in crowdsourcing NeurIPS 2016 A Field Model for Repairing 3D Shapes CVPR 2016 A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016 A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets COLING 2016 An Exact Approach to Learning Probabilistic Relational Model PGM 2016 Approximate Inference Using DC Programming For Collective Graphical Models AISTATS 2016 A Probabilistic Collaborative Representation Based Approach for Pattern Classification CVPR 2016 A Probabilistic Framework for Deep Learning NeurIPS 2016 A Probabilistic Framework for Real-time 3D Segmentation using Spatial, Temporal, and Semantic Cues RSS 2016