Ian Goodfellow

Ian Goodfellow (PhD in machine learning, University of Montreal, 2014) is a research scientist at Google. His research interests include most deep learning topics, especially generative models and machine learning security and privacy. He invented generative adversarial networks, was an influential early researcher studying adversarial examples, and is the lead author of the MIT Press textbook Deep Learning (www.deeplearningbook.org). He runs the Self-Organizing Conference on Machine Learning, which was founded at OpenAI in 2016. More information is available at www.iangoodfellow.com

Google Publications

Adversarial Spheres

Justin Gilmer, Luke Metz, Fartash Faghri, Sam Schoenholz, Maithra Raghu, Martin Wattenberg, Ian Goodfellow

ICLR Workshop (2018)
Ensemble Adversarial Training: Attacks and Defenses

Alex Kurakin, Dan Boneh, Florian Tramèr, Ian Goodfellow, Nicolas Papernot, Patrick McDaniel

ICLR (2018)
Gradient Penalties for Generative Adversarial Networks

Andrew Dai, Balaji Lakshminarayanan, Ian Goodfellow, Liam Fedus, Mihaela Rosca, Shakir Mohamed

ICLR (2018) (to appear)
MaskGAN: Better Text Generation via Filling in the ____

Andrew Dai, Ian Goodfellow, Liam Fedus

ICLR (2018) (to appear)
Realistic Evaluation of Semi-Supervised Learning Algorithms

Augustus Odena, Avital Oliver, Colin Raffel, Ekin Dogus Cubuk, Ian Goodfellow

ICLR Workshop (2018)
Thermometer Encoding: One Hot Way To Resist Adversarial Examples

Aurko Roy, Colin Raffel, Ian Goodfellow, Jacob Buckman

ICLR (2018)
Adversarial Attacks on Neural Network Policies

Sandy Huang, Nicolas Papernot, Ian Goodfellow, Yan Duan, Pieter Abbeel

arXiv (2017)
On the Protection of Private Information in Machine Learning Systems: Two Recent Approaches

Martín Abadi, Úlfar Erlingsson, Ian Goodfellow, H. Brendan McMahan, Nicolas Papernot, Ilya Mironov, Kunal Talwar, Li Zhang

IEEE 30th Computer Security Foundations Symposium (CSF), IEEE (2017), pp. 1-6
The Space of Transferable Adversarial Examples

Florian Tramèr, Nicolas Papernot, Ian Goodfellow, Dan Boneh, Patrick McDaniel

arXiv (2017)
Adversarial Autoencoders

Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow

International Conference on Learning Representations (2016)
Improving the Robustness of Deep Neural Networks via Stability Training

Stephan Zheng, Yang Song, Thomas Leung, Ian Goodfellow

CVPR'2016, IEEE (to appear)
Net2Net: Accelerating Learning via Knowledge Transfer

Tianqi Chen, Ian Goodfellow, Jonathon Shlens

International Conference on Learning Representations (2016)
Explaining and Harnessing Adversarial Examples

Ian Goodfellow, Jonathon Shlens, Christian Szegedy

International Conference on Learning Representations (2015)
Qualitatively Characterizing Neural Network Optimization Problems

Ian Goodfellow, Oriol Vinyals, Andrew Saxe

International Conference on Learning Representations (2015)
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng

tensorflow.org (2015)
Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks

Ian Goodfellow, Yaroslav Bulatov, Julian Ibarz, Sacha Arnoud, Vinay Shet

ICLR2014, ICLR2014 (to appear)

Previous Publications

Adversarial Machine Learning at Scale

Alexey Kurakin, Ian J. Goodfellow, Samy Bengio

ICLR (2017)
Adversarial Training Methods for Semi-Supervised Text Classification

Takeru Miyato, Andrew M. Dai, Ian Goodfellow

ICLR (2017)
Adversarial examples in the physical world

Alexey Kurakin, Ian Goodfellow, Samy Bengio

ICLR Workshop (2017)
Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data

Nicolas Papernot, Martín Abadi, Úlfar Erlingsson, Ian Goodfellow, Kunal Talwar

Proceedings of the International Conference on Learning Representations (2017)
Deep Learning with Differential Privacy

Martin Abadi, Andy Chu, Ian Goodfellow, Brendan McMahan, Ilya Mironov, Kunal Talwar, Li Zhang

23rd ACM Conference on Computer and Communications Security (ACM CCS) (2016), pp. 308-318
Unsupervised Learning for Physical Interaction through Video Prediction

Chelsea Finn, Ian Goodfellow, Sergey Levine

arXiv e-prints (2016)
Virtual Adversarial Training for Semi-Supervised Text Classification

Takeru Miayto, Andrew M. Dai, Ian Goodfellow

arXiv preprint (2016)
Intriguing properties of neural networks

Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, Rob Fergus

International Conference on Learning Representations (2014)
Help Me Help You: Interfaces for Personal Robots

Ian Goodfellow, Nate Koenig, Marius Muja, Caroline Pantofaru, Alex Sorokin, Leila Takayama

Proc. of Human Robot Interaction (HRI) (2010)
Measuring Invariances in Deep Networks

Ian Goodfellow, Quoc V. Le, Andrew Saxe, Honglak Lee, Andrew Y. Ng

NIPS (2009)

Ian Goodfellow

Co-Authors

Google Publications

Previous Publications