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Realistic Evaluation of Deep Semi-Supervised Learning Algorithms

Oct 26, 2018
Avital Oliver, Augustus Odena, Colin Raffel, Ekin D. Cubuk, Ian J. Goodfellow

* NIPS 2018 Proceedings 

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Qualitatively characterizing neural network optimization problems

May 21, 2015
Ian J. Goodfellow, Oriol Vinyals, Andrew M. Saxe

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On distinguishability criteria for estimating generative models

May 21, 2015
Ian J. Goodfellow

* This version adds a figure that appeared on the poster at ICLR, changes the template to say that the paper was accepted as a workshop contribution (previously it was under a review as a conference submission), and fixes some typos 

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Explaining and Harnessing Adversarial Examples

Mar 20, 2015
Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy

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An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks

Mar 04, 2015
Ian J. Goodfellow, Mehdi Mirza, Da Xiao, Aaron Courville, Yoshua Bengio

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On the Challenges of Physical Implementations of RBMs

Oct 24, 2014
Vincent Dumoulin, Ian J. Goodfellow, Aaron Courville, Yoshua Bengio

* Proc. AAAI 2014, pp. 1199-1205 

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Generative Adversarial Networks

Jun 10, 2014
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio

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Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks

Apr 14, 2014
Ian J. Goodfellow, Yaroslav Bulatov, Julian Ibarz, Sacha Arnoud, Vinay Shet

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An empirical analysis of dropout in piecewise linear networks

Jan 02, 2014
David Warde-Farley, Ian J. Goodfellow, Aaron Courville, Yoshua Bengio

* Extensive updates; 8 pages plus acknowledgements/references 

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Maxout Networks

Sep 20, 2013
Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville, Yoshua Bengio

* JMLR WCP 28 (3): 1319-1327, 2013 
* This is the version of the paper that appears in ICML 2013 

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Pylearn2: a machine learning research library

Aug 20, 2013
Ian J. Goodfellow, David Warde-Farley, Pascal Lamblin, Vincent Dumoulin, Mehdi Mirza, Razvan Pascanu, James Bergstra, Frédéric Bastien, Yoshua Bengio

* 9 pages 

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Challenges in Representation Learning: A report on three machine learning contests

Jul 01, 2013
Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron Courville, Mehdi Mirza, Ben Hamner, Will Cukierski, Yichuan Tang, David Thaler, Dong-Hyun Lee, Yingbo Zhou, Chetan Ramaiah, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Zhang Chuang, Yoshua Bengio

* 8 pages, 2 figures 

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Joint Training Deep Boltzmann Machines for Classification

May 01, 2013
Ian J. Goodfellow, Aaron Courville, Yoshua Bengio

* Major revision with new techniques and experiments. This version includes new material put on the poster for the ICLR workshop 

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Piecewise Linear Multilayer Perceptrons and Dropout

Jan 22, 2013
Ian J. Goodfellow

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Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery

Apr 03, 2012
Ian J. Goodfellow, Aaron Courville, Yoshua Bengio

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