The Kernel Mixture Network: A Nonparametric Method for Conditional Density Estimation of Continuous Random Variables

19 May 2017

Papers citing "The Kernel Mixture Network: A Nonparametric Method for Conditional Density Estimation of Continuous Random Variables"

10 / 10 papers shown

Title
Doubly Robust Proximal Causal Learning for Continuous Treatments Yong Wu Yanwei Fu Shouyan Wang Xinwei Sun 26 1 0 22 Sep 2023
Ensemble weather forecast post-processing with a flexible probabilistic neural network approach P. Mlakar J. Merse Jana Faganeli Pucer 17 4 0 29 Mar 2023
A Causal Approach to Detecting Multivariate Time-series Anomalies and Root Causes Wenzhuo Yang Kun Zhang S. Hoi AI4TS CML 27 9 0 30 Jun 2022
Probabilistic Conformal Prediction Using Conditional Random Samples Zhendong Wang Ruijiang Gao Mingzhang Yin Mingyuan Zhou David M. Blei TPM 36 22 0 14 Jun 2022
Conditional Measurement Density Estimation in Sequential Monte Carlo via Normalizing Flow Xiongjie Chen Yunpeng Li 15 6 0 16 Mar 2022
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments Lizhen Nie Mao Ye Qiang Liu D. Nicolae CML 17 68 0 14 Mar 2021
Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks Jonas Rothfuss Fabio Ferreira Simon Walther Maxim Ulrich TPM 24 73 0 03 Mar 2019
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 251 1,811 0 25 Nov 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 253 3,239 0 24 Nov 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 233 2,547 0 25 Jan 2016