Density Estimation

Strudel: Learning Structured-Decomposable Probabilistic Circuits PGM 2020 Sum-Product-Transform Networks: Exploiting Symmetries using Invertible Transformations PGM 2020 The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians COLT 2020 A Locally Adaptive Normal Distribution NeurIPS 2016 Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation NeurIPS 2016 Density Estimation via Discrepancy Based Adaptive Sequential Partition NeurIPS 2016 Efficient Nonparametric Smoothness Estimation NeurIPS 2016 Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators NeurIPS 2016 Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences NeurIPS 2016 On the Estimation of the Gradient Lines of a Density and the Consistency of the Mean-Shift Algorithm JMLR 2016 Sorting out typicality with the inverse moment matrix SOS polynomial NeurIPS 2016 Competitive Distribution Estimation: Why is Good-Turing Good NeurIPS 2015 Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations NeurIPS 2015 Optimal Ridge Detection using Coverage Risk NeurIPS 2015 Blossom Tree Graphical Models NeurIPS 2014 Exponential Concentration of a Density Functional Estimator NeurIPS 2014 Factoring Variations in Natural Images with Deep Gaussian Mixture Models NeurIPS 2014 Near-Optimal Density Estimation in Near-Linear Time Using Variable-Width Histograms NeurIPS 2014 Near-Optimal-Sample Estimators for Spherical Gaussian Mixtures NeurIPS 2014 Optimal rates for k-NN density and mode estimation NeurIPS 2014 Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space NeurIPS 2014 Sensory Integration and Density Estimation NeurIPS 2014 Cluster Trees on Manifolds NeurIPS 2013 Density estimation from unweighted k-nearest neighbor graphs: a roadmap NeurIPS 2013 Multiscale Dictionary Learning for Estimating Conditional Distributions NeurIPS 2013