Probabilistic Modeling

Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models JMLR 2018 Power-law efficient neural codes provide general link between perceptual bias and discriminability NeurIPS 2018 Principled Selection of Hyperparameters in the Latent Dirichlet Allocation Model JMLR 2018 Probabilistic Boolean Tensor Decomposition ICML 2018 Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures ACL 2018 Probabilistic Joint Face-Skull Modelling for Facial Reconstruction CVPR 2018 Probabilistic Plant Modeling via Multi-View Image-to-Image Translation CVPR 2018 Prometheus : Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks PGM 2018 Provable Gaussian Embedding with One Observation NeurIPS 2018 Proximal Graphical Event Models NeurIPS 2018 Ranking Distributions based on Noisy Sorting ICML 2018 Representations of Bayesian networks by low-rank models PGM 2018 Representing and Learning High Dimensional Data With the Optimal Transport Map From a Probabilistic Viewpoint CVPR 2018 Robust and Scalable Models of Microbiome Dynamics ICML 2018 Scalable Bayes via Barycenter in Wasserstein Space JMLR 2018 Scaling the Poisson GLM to massive neural datasets through polynomial approximations NeurIPS 2018 Scaling up Data Augmentation MCMC via Calibration JMLR 2018 Semi-Supervised Prediction-Constrained Topic Models AISTATS 2018 Sparse Estimation in Ising Model via Penalized Monte Carlo Methods JMLR 2018 Sparse Learning in Gaussian Chain Graphs for State Space Models PGM 2018 State-by-state Minimax Adaptive Estimation for Nonparametric Hidden {M}arkov Models JMLR 2018 Stochastic Wasserstein Barycenters ICML 2018 Structured Gaussian Processes with Twin Multiple Kernel Learning ACML 2018 Structure Learning Under Missing Data PGM 2018 Sum-Product-Quotient Networks AISTATS 2018