Ian J. Goodfellow

109 papers A* 16A 2Journal 59Unranked 31

Year	Rank	Type	Title / Venue / Authors
2020	J	`jnl`	Creating High Resolution Images with a Latent Adversarial Generator. CoRR David Berthelot, Peyman Milanfar, Ian J. Goodfellow
2020	A*	`conf`	Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming. NeurIPS Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin, Aditi Raghunathan, Jonathan Uesato, Rudy Bunel, Shreya Shankar, Jacob Steinhardt, Ian J. Goodfellow, Percy Liang, Pushmeet Kohli
2020	J	`jnl`	Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming. CoRR Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin, Aditi Raghunathan, Jonathan Uesato, Rudy Bunel, Shreya Shankar, Jacob Steinhardt, Ian J. Goodfellow, Percy Liang, Pushmeet Kohli
2020	J	`jnl`	Generative adversarial networks. Commun. ACM Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, Yoshua Bengio
2019	A*	`conf`	A Domain Agnostic Measure for Monitoring and Evaluating GANs. NeurIPS Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Nathanaël Perraudin, Ian J. Goodfellow, Thomas Hofmann, Andreas Krause
2019	J	`jnl`	A Research Agenda: Dynamic Models to Defend Against Correlated Attacks. CoRR Ian J. Goodfellow
2019	—	`conf`	Adversarial Reprogramming of Neural Networks. ICLR (Poster) Gamaleldin F. Elsayed, Ian J. Goodfellow, Jascha Sohl-Dickstein
2019	—	`conf`	Discriminator Rejection Sampling. ICLR (Poster) Samaneh Azadi, Catherine Olsson, Trevor Darrell, Ian J. Goodfellow, Augustus Odena
2019	A*	`conf`	Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition. ICML Yao Qin, Nicholas Carlini, Garrison W. Cottrell, Ian J. Goodfellow, Colin Raffel
2019	J	`jnl`	Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition. CoRR Yao Qin, Nicholas Carlini, Ian J. Goodfellow, Garrison W. Cottrell, Colin Raffel
2019	A*	`conf`	MixMatch: A Holistic Approach to Semi-Supervised Learning. NeurIPS David Berthelot, Nicholas Carlini, Ian J. Goodfellow, Nicolas Papernot, Avital Oliver, Colin Raffel
2019	J	`jnl`	MixMatch: A Holistic Approach to Semi-Supervised Learning. CoRR David Berthelot, Nicholas Carlini, Ian J. Goodfellow, Nicolas Papernot, Avital Oliver, Colin Raffel
2019	J	`jnl`	On Evaluating Adversarial Robustness. CoRR Nicholas Carlini, Anish Athalye, Nicolas Papernot, Wieland Brendel, Jonas Rauber, Dimitris Tsipras, Ian J. Goodfellow, Aleksander Madry, Alexey Kurakin
2019	A*	`conf`	Self-Attention Generative Adversarial Networks. ICML Han Zhang, Ian J. Goodfellow, Dimitris N. Metaxas, Augustus Odena
2019	A*	`conf`	TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing. ICML Augustus Odena, Catherine Olsson, David G. Andersen, Ian J. Goodfellow
2019	—	`conf`	Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer. ICLR (Poster) David Berthelot, Colin Raffel, Aurko Roy, Ian J. Goodfellow
2018	J	`jnl`	Adversarial Attacks and Defences Competition. CoRR Alexey Kurakin, Ian J. Goodfellow, Samy Bengio, Yinpeng Dong, Fangzhou Liao, Ming Liang, Tianyu Pang, Jun Zhu, Xiaolin Hu, Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, Alan L. Yuille, Sangxia Huang, Yao Zhao, Yuzhe Zhao, Zhonglin Han, Junjiajia Long, Yerkebulan Berdibekov, Takuya Akiba, Seiya Tokui, Motoki Abe
2018	A*	`conf`	Adversarial Examples that Fool both Computer Vision and Time-Limited Humans. NeurIPS Gamaleldin F. Elsayed, Shreya Shankar, Brian Cheung, Nicolas Papernot, Alexey Kurakin, Ian J. Goodfellow, Jascha Sohl-Dickstein
2018	J	`jnl`	Adversarial Examples that Fool both Human and Computer Vision. CoRR Gamaleldin F. Elsayed, Shreya Shankar, Brian Cheung, Nicolas Papernot, Alex Kurakin, Ian J. Goodfellow, Jascha Sohl-Dickstein
2018	J	`jnl`	Adversarial Logit Pairing. CoRR Harini Kannan, Alexey Kurakin, Ian J. Goodfellow
2018	J	`jnl`	Adversarial Reprogramming of Neural Networks. CoRR Gamaleldin F. Elsayed, Ian J. Goodfellow, Jascha Sohl-Dickstein
2018	—	`conf`	Adversarial Spheres. ICLR (Workshop) Justin Gilmer, Luke Metz, Fartash Faghri, Samuel S. Schoenholz, Maithra Raghu, Martin Wattenberg, Ian J. Goodfellow
2018	J	`jnl`	Adversarial Spheres. CoRR Justin Gilmer, Luke Metz, Fartash Faghri, Samuel S. Schoenholz, Maithra Raghu, Martin Wattenberg, Ian J. Goodfellow
2018	J	`jnl`	Defense Against the Dark Arts: An overview of adversarial example security research and future research directions. CoRR Ian J. Goodfellow
2018	J	`jnl`	Discriminator Rejection Sampling. CoRR Samaneh Azadi, Catherine Olsson, Trevor Darrell, Ian J. Goodfellow, Augustus Odena
2018	—	`conf`	Ensemble Adversarial Training: Attacks and Defenses. ICLR (Poster) Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Ian J. Goodfellow, Dan Boneh, Patrick D. McDaniel
2018	J	`jnl`	Gradient Masking Causes CLEVER to Overestimate Adversarial Perturbation Size. CoRR Ian J. Goodfellow
2018	A*	`conf`	Is Generator Conditioning Causally Related to GAN Performance? ICML Augustus Odena, Jacob Buckman, Catherine Olsson, Tom B. Brown, Christopher Olah, Colin Raffel, Ian J. Goodfellow
2018	J	`jnl`	Is Generator Conditioning Causally Related to GAN Performance? CoRR Augustus Odena, Jacob Buckman, Catherine Olsson, Tom B. Brown, Christopher Olah, Colin Raffel, Ian J. Goodfellow
2018	—	`conf`	Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values. ICLR (Workshop) Julius Adebayo, Justin Gilmer, Ian J. Goodfellow, Been Kim
2018	J	`jnl`	Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values. CoRR Julius Adebayo, Justin Gilmer, Ian J. Goodfellow, Been Kim
2018	J	`jnl`	Making machine learning robust against adversarial inputs. Commun. ACM Ian J. Goodfellow, Patrick D. McDaniel, Nicolas Papernot
2018	—	`conf`	Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step. ICLR (Poster) William Fedus, Mihaela Rosca, Balaji Lakshminarayanan, Andrew M. Dai, Shakir Mohamed, Ian J. Goodfellow
2018	J	`jnl`	MaskGAN: Better Text Generation via Filling in the ______. CoRR William Fedus, Ian J. Goodfellow, Andrew M. Dai
2018	—	`conf`	MaskGAN: Better Text Generation via Filling in the _______. ICLR (Poster) William Fedus, Ian J. Goodfellow, Andrew M. Dai
2018	J	`jnl`	Motivating the Rules of the Game for Adversarial Example Research. CoRR Justin Gilmer, Ryan P. Adams, Ian J. Goodfellow, David G. Andersen, George E. Dahl
2018	J	`jnl`	New CleverHans Feature: Better Adversarial Robustness Evaluations with Attack Bundling. CoRR Ian J. Goodfellow
2018	A*	`conf`	Realistic Evaluation of Deep Semi-Supervised Learning Algorithms. NeurIPS Avital Oliver, Augustus Odena, Colin Raffel, Ekin Dogus Cubuk, Ian J. Goodfellow
2018	J	`jnl`	Realistic Evaluation of Deep Semi-Supervised Learning Algorithms. CoRR Avital Oliver, Augustus Odena, Colin Raffel, Ekin D. Cubuk, Ian J. Goodfellow
2018	—	`conf`	Realistic Evaluation of Semi-Supervised Learning Algorithms. ICLR (Workshop) Avital Oliver, Augustus Odena, Colin Raffel, Ekin D. Cubuk, Ian J. Goodfellow
2018	A*	`conf`	Sanity Checks for Saliency Maps. NeurIPS Julius Adebayo, Justin Gilmer, Michael Muelly, Ian J. Goodfellow, Moritz Hardt, Been Kim
2018	J	`jnl`	Sanity Checks for Saliency Maps. CoRR Julius Adebayo, Justin Gilmer, Michael Muelly, Ian J. Goodfellow, Moritz Hardt, Been Kim
2018	J	`jnl`	Self-Attention Generative Adversarial Networks. CoRR Han Zhang, Ian J. Goodfellow, Dimitris N. Metaxas, Augustus Odena
2018	J	`jnl`	Skill Rating for Generative Models. CoRR Catherine Olsson, Surya Bhupatiraju, Tom B. Brown, Augustus Odena, Ian J. Goodfellow
2018	J	`jnl`	TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing. CoRR Augustus Odena, Ian J. Goodfellow
2018	—	`conf`	Thermometer Encoding: One Hot Way To Resist Adversarial Examples. ICLR (Poster) Jacob Buckman, Aurko Roy, Colin Raffel, Ian J. Goodfellow
2018	J	`jnl`	Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer. CoRR David Berthelot, Colin Raffel, Aurko Roy, Ian J. Goodfellow
2018	J	`jnl`	Unrestricted Adversarial Examples. CoRR Tom B. Brown, Nicholas Carlini, Chiyuan Zhang, Catherine Olsson, Paul F. Christiano, Ian J. Goodfellow
2017	—	`conf`	Adversarial Attacks on Neural Network Policies. ICLR (Workshop) Sandy H. Huang, Nicolas Papernot, Ian J. Goodfellow, Yan Duan, Pieter Abbeel
2017	J	`jnl`	Adversarial Attacks on Neural Network Policies. CoRR Sandy H. Huang, Nicolas Papernot, Ian J. Goodfellow, Yan Duan, Pieter Abbeel
2017	—	`conf`	Adversarial Machine Learning at Scale. ICLR (Poster) Alexey Kurakin, Ian J. Goodfellow, Samy Bengio
2017	—	`conf`	Adversarial Training Methods for Semi-Supervised Text Classification. ICLR (Poster) Takeru Miyato, Andrew M. Dai, Ian J. Goodfellow
2017	—	`conf`	Adversarial examples in the physical world. ICLR (Workshop) Alexey Kurakin, Ian J. Goodfellow, Samy Bengio
2017	J	`jnl`	Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step. CoRR William Fedus, Mihaela Rosca, Balaji Lakshminarayanan, Andrew M. Dai, Shakir Mohamed, Ian J. Goodfellow
2017	J	`jnl`	NIPS 2016 Tutorial: Generative Adversarial Networks. CoRR Ian J. Goodfellow
2017	J	`jnl`	On the Protection of Private Information in Machine Learning Systems: Two Recent Approaches. CoRR Martín Abadi, Úlfar Erlingsson, Ian J. Goodfellow, H. Brendan McMahan, Ilya Mironov, Nicolas Papernot, Kunal Talwar, Li Zhang
2017	A	`conf`	On the Protection of Private Information in Machine Learning Systems: Two Recent Approches. CSF Martín Abadi, Úlfar Erlingsson, Ian J. Goodfellow, H. Brendan McMahan, Ilya Mironov, Nicolas Papernot, Kunal Talwar, Li Zhang
2017	A	`conf`	Practical Black-Box Attacks against Machine Learning. AsiaCCS Nicolas Papernot, Patrick D. McDaniel, Ian J. Goodfellow, Somesh Jha, Z. Berkay Celik, Ananthram Swami
2017	—	`conf`	Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data. ICLR Nicolas Papernot, Martín Abadi, Úlfar Erlingsson, Ian J. Goodfellow, Kunal Talwar
2017	J	`jnl`	The Space of Transferable Adversarial Examples. CoRR Florian Tramèr, Nicolas Papernot, Ian J. Goodfellow, Dan Boneh, Patrick D. McDaniel
2016	J	`jnl`	Adversarial Machine Learning at Scale. CoRR Alexey Kurakin, Ian J. Goodfellow, Samy Bengio
2016	J	`jnl`	Adversarial examples in the physical world. CoRR Alexey Kurakin, Ian J. Goodfellow, Samy Bengio
2016	A*	`conf`	Deep Learning with Differential Privacy. CCS Martín Abadi, Andy Chu, Ian J. Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, Li Zhang
2016	J	`jnl`	Deep Learning with Differential Privacy. CoRR Martín Abadi, Andy Chu, Ian J. Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, Li Zhang
2016	—	`book`	Deep Learning. Ian J. Goodfellow, Yoshua Bengio, Aaron C. Courville
2016	—	`conf`	Improved Techniques for Training GANs. NIPS Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen
2016	J	`jnl`	Improved Techniques for Training GANs. CoRR Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen
2016	A*	`conf`	Improving the Robustness of Deep Neural Networks via Stability Training. CVPR Stephan Zheng, Yang Song, Thomas Leung, Ian J. Goodfellow
2016	J	`jnl`	Improving the Robustness of Deep Neural Networks via Stability Training. CoRR Stephan Zheng, Yang Song, Thomas Leung, Ian J. Goodfellow
2016	A*	`conf`	Net2Net: Accelerating Learning via Knowledge Transfer. ICLR Tianqi Chen, Ian J. Goodfellow, Jonathon Shlens
2016	J	`jnl`	Practical Black-Box Attacks against Deep Learning Systems using Adversarial Examples. CoRR Nicolas Papernot, Patrick D. McDaniel, Ian J. Goodfellow, Somesh Jha, Z. Berkay Celik, Ananthram Swami
2016	J	`jnl`	Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data. CoRR Nicolas Papernot, Martín Abadi, Úlfar Erlingsson, Ian J. Goodfellow, Kunal Talwar
2016	J	`jnl`	TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. CoRR Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Gregory S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian J. Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Józefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Gordon Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul A. Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda B. Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng
2016	J	`jnl`	Theano: A Python framework for fast computation of mathematical expressions. CoRR Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang
2016	J	`jnl`	Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples. CoRR Nicolas Papernot, Patrick D. McDaniel, Ian J. Goodfellow
2016	—	`conf`	Unsupervised Learning for Physical Interaction through Video Prediction. NIPS Chelsea Finn, Ian J. Goodfellow, Sergey Levine
2016	J	`jnl`	Unsupervised Learning for Physical Interaction through Video Prediction. CoRR Chelsea Finn, Ian J. Goodfellow, Sergey Levine
2016	J	`jnl`	Virtual Adversarial Training for Semi-Supervised Text Classification. CoRR Takeru Miyato, Andrew M. Dai, Ian J. Goodfellow
2016	J	`jnl`	cleverhans v0.1: an adversarial machine learning library. CoRR Ian J. Goodfellow, Nicolas Papernot, Patrick D. McDaniel
2015	J	`jnl`	Adversarial Autoencoders. CoRR Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian J. Goodfellow
2015	J	`jnl`	Challenges in representation learning: A report on three machine learning contests. Neural Networks Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron C. Courville, Mehdi Mirza, Benjamin Hamner, William 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 Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio
2015	J	`jnl`	Efficient Per-Example Gradient Computations. CoRR Ian J. Goodfellow
2015	—	`conf`	Explaining and Harnessing Adversarial Examples. ICLR (Poster) Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy
2015	—	`conf`	On distinguishability criteria for estimating generative models ICLR (Workshop) Ian J. Goodfellow
2015	—	`conf`	Qualitatively characterizing neural network optimization problems. ICLR Ian J. Goodfellow, Oriol Vinyals
2014	—	`conf`	An Empirical Investigation of Catastrophic Forgeting in Gradient-Based Neural Networks. ICLR (Poster) Ian J. Goodfellow, Mehdi Mirza, Xia Da, Aaron C. Courville, Yoshua Bengio
2014	—	`conf`	An empirical analysis of dropout in piecewise linear networks. ICLR (Poster) David Warde-Farley, Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2014	—	`conf`	Generative Adversarial Nets. NIPS Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, Yoshua Bengio
2014	J	`jnl`	Generative Adversarial Networks. CoRR Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, Yoshua Bengio
2014	—	`conf`	Intriguing properties of neural networks. ICLR (Poster) Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, Rob Fergus
2014	—	`conf`	Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks. ICLR Ian J. Goodfellow, Yaroslav Bulatov, Julian Ibarz, Sacha Arnoud, Vinay D. Shet
2014	A*	`conf`	On the Challenges of Physical Implementations of RBMs. AAAI Vincent Dumoulin, Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2013	—	`conf`	Challenges in Representation Learning: A Report on Three Machine Learning Contests. ICONIP (3) Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron C. Courville, Mehdi Mirza, Benjamin Hamner, William 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 Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio
2013	J	`jnl`	Challenges in Representation Learning: A report on three machine learning contests. CoRR Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron C. Courville, Mehdi Mirza, Benjamin Hamner, William 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 Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio
2013	—	`conf`	Joint Training Deep Boltzmann Machines for Classification ICLR (Workshop) Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2013	J	`jnl`	Maxout Networks CoRR Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron C. Courville, Yoshua Bengio
2013	—	`conf`	Maxout Networks. ICML (3) Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron C. Courville, Yoshua Bengio
2013	—	`conf`	Multi-Prediction Deep Boltzmann Machines. NIPS Ian J. Goodfellow, Mehdi Mirza, Aaron C. Courville, Yoshua Bengio
2013	J	`jnl`	On the Challenges of Physical Implementations of RBMs. CoRR Vincent Dumoulin, Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2013	J	`jnl`	Piecewise Linear Multilayer Perceptrons and Dropout CoRR Ian J. Goodfellow
2013	J	`jnl`	Pylearn2: a machine learning research library. CoRR Ian J. Goodfellow, David Warde-Farley, Pascal Lamblin, Vincent Dumoulin, Mehdi Mirza, Razvan Pascanu, James Bergstra, Frédéric Bastien, Yoshua Bengio
2013	J	`jnl`	Scaling Up Spike-and-Slab Models for Unsupervised Feature Learning. IEEE Trans. Pattern Anal. Mach. Intell. Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2012	J	`jnl`	Joint Training of Deep Boltzmann Machines CoRR Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2012	A*	`conf`	Large-Scale Feature Learning With Spike-and-Slab Sparse Coding. ICML Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2012	J	`jnl`	Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery CoRR Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
2012	J	`jnl`	Theano: new features and speed improvements CoRR Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, James Bergstra, Ian J. Goodfellow, Arnaud Bergeron, Nicolas Bouchard, David Warde-Farley, Yoshua Bengio
2012	—	`conf`	Unsupervised and Transfer Learning Challenge: a Deep Learning Approach. ICML Unsupervised and Transfer Learning Grégoire Mesnil, Yann N. Dauphin, Xavier Glorot, Salah Rifai, Yoshua Bengio, Ian J. Goodfellow, Erick Lavoie, Xavier Muller, Guillaume Desjardins, David Warde-Farley, Pascal Vincent, Aaron C. Courville, James Bergstra
2010	A*	`conf`	Help me help you: interfaces for personal robots. HRI Ian J. Goodfellow, Nate Koenig, Marius Muja, Caroline Pantofaru, Alexander Sorokin, Leila Takayama
2009	—	`conf`	Measuring Invariances in Deep Networks. NIPS Ian J. Goodfellow, Quoc V. Le, Andrew M. Saxe, Honglak Lee, Andrew Y. Ng