Expected Information Maximization: Using the I-Projection for Mixture Density Estimation

23 January 2020

Papers citing "Expected Information Maximization: Using the I-Projection for Mixture Density Estimation"

22 / 22 papers shown

Title
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 422 10,591 0 17 Feb 2020
Adversarial Learning of a Sampler Based on an Unnormalized Distribution Chunyuan Li Ke Bai Jianqiao Li Guoyin Wang Changyou Chen Lawrence Carin 132 10 0 03 Jan 2019
Maximum a Posteriori Policy Optimisation A. Abdolmaleki Jost Tobias Springenberg Yuval Tassa Rémi Munos N. Heess Martin Riedmiller 71 477 0 14 Jun 2018
On GANs and GMMs Eitan Richardson Yair Weiss GAN 172 151 0 31 May 2018
Symmetric Variational Autoencoder and Connections to Adversarial Learning Liqun Chen Shuyang Dai Yunchen Pu Chunyuan Li Weiyao Wang Lawrence Carin DRL GAN 78 71 0 06 Sep 2017
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 517 19,065 0 20 Jul 2017
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 207 9,548 0 31 Mar 2017
Wasserstein GAN Martín Arjovsky Soumith Chintala Léon Bottou GAN 172 4,826 0 26 Jan 2017
Improved generator objectives for GANs Ben Poole Alexander A. Alemi Jascha Narain Sohl-Dickstein A. Angelova 56 69 0 08 Dec 2016
Generative Adversarial Nets from a Density Ratio Estimation Perspective Masatoshi Uehara Issei Sato Masahiro Suzuki Kotaro Nakayama Y. Matsuo GAN 83 104 0 10 Oct 2016
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets Xi Chen Yan Duan Rein Houthooft John Schulman Ilya Sutskever Pieter Abbeel GAN 159 4,235 0 12 Jun 2016
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization Sebastian Nowozin Botond Cseke Ryota Tomioka GAN 154 1,656 0 02 Jun 2016
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Zhiwen Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 433 18,361 0 27 May 2016
Auxiliary Deep Generative Models Lars Maaløe C. Sønderby Søren Kaae Sønderby Ole Winther DRL GAN 75 451 0 17 Feb 2016
How (not) to Train your Generative Model: Scheduled Sampling, Likelihood, Adversary? Ferenc Huszár OOD DiffM GAN 87 297 0 16 Nov 2015
Hierarchical Variational Models Rajesh Ranganath Dustin Tran David M. Blei DRL VLM 83 338 0 07 Nov 2015
Trust Region Policy Optimization John Schulman Sergey Levine Philipp Moritz Michael I. Jordan Pieter Abbeel 277 6,776 0 19 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,115 0 22 Dec 2014
Minimum scoring rule inference A. Dawid M. Musio L. Ventura 65 68 0 16 Mar 2014
Inferring Parameters and Structure of Latent Variable Models by Variational Bayes H. Attias CML BDL 71 666 0 23 Jan 2013
Relative Density-Ratio Estimation for Robust Distribution Comparison M. Yamada Taiji Suzuki Takafumi Kanamori Hirotaka Hachiya Masashi Sugiyama 92 221 0 23 Jun 2011
Estimating divergence functionals and the likelihood ratio by convex risk minimization X. Nguyen Martin J. Wainwright Michael I. Jordan 225 803 0 04 Sep 2008