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Probabilistic Modeling

2591 directly classified papers

Papers per year

Papers

Variational Dependent Multi-output Gaussian Process Dynamical Systems JMLR 2016
Herded Gibbs Sampling JMLR 2016
Variational Inference in Mixed Probabilistic Submodular Models NIPS 2016
Learning under uncertainty: a comparison between R-W and Bayesian approach NIPS 2016
A Field Model for Repairing 3D Shapes CVPR 2016
RAID-G: Robust Estimation of Approximate Infinite Dimensional Gaussian With Application to Material Recognition CVPR 2016
Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models NIPS 2016
Edge-exchangeable graphs and sparsity NIPS 2016
Sequential Neural Models with Stochastic Layers NIPS 2016
Efficient Sampling for k-Determinantal Point Processes AISTATS 2016
Disease Trajectory Maps NIPS 2016
Estimating SE(3) elements using a dual quaternion based linear Kalman filter RSS 2016
Gaussian Processes for Survival Analysis NIPS 2016
Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model NIPS 2016
Discriminative Structure Learning of Arithmetic Circuits AISTATS 2016
Survey Propagation beyond Constraint Satisfaction Problems AISTATS 2016
Generalized Ideal Parent (GIP): Discovering non-Gaussian Hidden Variables AISTATS 2016
Inference Networks for Sequential Monte Carlo in Graphical Models ICML 2016
Energetic Natural Gradient Descent ICML 2016
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations ICML 2016
Conditional Bernoulli Mixtures for Multi-label Classification ICML 2016
Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies ICML 2016
Isotonic Hawkes Processes ICML 2016
PAC learning of Probabilistic Automaton based on the Method of Moments ICML 2016
A Probabilistic Framework for Real-time 3D Segmentation using Spatial, Temporal, and Semantic Cues RSS 2016