Implicit Maximum Likelihood Estimation

24 September 2018

Papers citing "Implicit Maximum Likelihood Estimation"

33 / 33 papers shown

Title
Conditional Distribution Quantization in Machine Learning Blaise Delattre Sylvain Delattre Alexandre Verine Alexandre Allauzen 107 0 0 11 Feb 2025
Balancing Act: Distribution-Guided Debiasing in Diffusion Models Rishubh Parihar Abhijnya Bhat Abhipsa Basu Saswat Mallick Jogendra Nath Kundu R. V. Babu 87 18 0 28 Feb 2024
Do GANs actually learn the distribution? An empirical study Sanjeev Arora Yi Zhang 41 191 0 26 Jun 2017
Dualing GANs Yujia Li Alex Schwing Kuan-Chieh Wang R. Zemel GAN 47 20 0 19 Jun 2017
The Numerics of GANs L. Mescheder Sebastian Nowozin Andreas Geiger GAN 75 456 0 30 May 2017
Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training M. Sinn Ambrish Rawat GAN 35 21 0 25 May 2017
Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models Aditya Grover Manik Dhar Stefano Ermon GAN 61 24 0 24 May 2017
Generalization and Equilibrium in Generative Adversarial Nets (GANs) Sanjeev Arora Rong Ge Yingyu Liang Tengyu Ma Yi Zhang GAN 54 687 0 02 Mar 2017
Fast k-Nearest Neighbour Search via Prioritized DCI Ke Li Jitendra Malik 20 34 0 01 Mar 2017
Boundary-Seeking Generative Adversarial Networks R. Devon Hjelm Athul Paul Jacob Tong Che Adam Trischler Kyunghyun Cho Yoshua Bengio GAN 48 170 0 27 Feb 2017
Towards Principled Methods for Training Generative Adversarial Networks Martín Arjovsky M. Nault GAN 77 2,102 0 17 Jan 2017
On the Quantitative Analysis of Decoder-Based Generative Models Yuhuai Wu Yuri Burda Ruslan Salakhutdinov Roger C. Grosse GAN 73 223 0 14 Nov 2016
Learning in Implicit Generative Models S. Mohamed Balaji Lakshminarayanan GAN 130 415 0 11 Oct 2016
Energy-based Generative Adversarial Network Jiaqi Zhao Michaël Mathieu Yann LeCun GAN 124 1,112 0 11 Sep 2016
Improved Techniques for Training GANs Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen GAN 401 8,999 0 10 Jun 2016
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization Sebastian Nowozin Botond Cseke Ryota Tomioka GAN 102 1,648 0 02 Jun 2016
Adversarially Learned Inference Vincent Dumoulin Ishmael Belghazi Ben Poole Olivier Mastropietro Alex Lamb Martín Arjovsky Aaron Courville GAN 62 1,312 0 02 Jun 2016
Asynchrony begets Momentum, with an Application to Deep Learning Jeff Donahue Philipp Krahenbuhl Stefan Hadjis Christopher Ré 85 1,827 0 31 May 2016
Generating Images with Perceptual Similarity Metrics based on Deep Networks Alexey Dosovitskiy Thomas Brox DRL GAN 81 1,137 0 08 Feb 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 415 2,563 0 25 Jan 2016
Fast k-Nearest Neighbour Search via Dynamic Continuous Indexing Ke Li Jitendra Malik 67 31 0 01 Dec 2015
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Alec Radford Luke Metz Soumith Chintala GAN OOD 234 13,968 0 19 Nov 2015
How (not) to Train your Generative Model: Scheduled Sampling, Likelihood, Adversary? Ferenc Huszár OOD DiffM GAN 67 296 0 16 Nov 2015
A note on the evaluation of generative models Lucas Theis Aaron van den Oord Matthias Bethge EGVM 85 1,142 0 05 Nov 2015
Importance Weighted Autoencoders Yuri Burda Roger C. Grosse Ruslan Salakhutdinov BDL 221 1,240 0 01 Sep 2015
Training generative neural networks via Maximum Mean Discrepancy optimization Gintare Karolina Dziugaite Daniel M. Roy Zoubin Ghahramani GAN 82 528 0 14 May 2015
Generative Moment Matching Networks Yujia Li Kevin Swersky R. Zemel OOD GAN 93 844 0 10 Feb 2015
Likelihood-free inference via classification Michael U. Gutmann Ritabrata Dutta Samuel Kaski J. Corander 120 63 0 18 Jul 2014
Stochastic Backpropagation and Approximate Inference in Deep Generative Models Danilo Jimenez Rezende S. Mohamed Daan Wierstra BDL 63 139 0 16 Jan 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 378 16,962 0 20 Dec 2013
Deep Generative Stochastic Networks Trainable by Backprop Yoshua Bengio Eric Thibodeau-Laufer Guillaume Alain J. Yosinski BDL 114 396 0 05 Jun 2013
Better Mixing via Deep Representations Yoshua Bengio Grégoire Mesnil Yann N. Dauphin Salah Rifai 70 339 0 18 Jul 2012
A Kernel Method for the Two-Sample Problem Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alex Smola 184 2,352 0 15 May 2008