Ian J. Goodfellow

According to our database1, Ian J. Goodfellow authored at least 81 papers between 2009 and 2020.

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Bibliography

2020
Creating High Resolution Images with a Latent Adversarial Generator.
CoRR, 2020

2019
A Research Agenda: Dynamic Models to Defend Against Correlated Attacks.
CoRR, 2019

On Evaluating Adversarial Robustness.
CoRR, 2019

MixMatch: A Holistic Approach to Semi-Supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Self-Attention Generative Adversarial Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition.
Proceedings of the 36th International Conference on Machine Learning, 2019

TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing.
Proceedings of the 36th International Conference on Machine Learning, 2019

Adversarial Reprogramming of Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer.
Proceedings of the 7th International Conference on Learning Representations, 2019

Discriminator Rejection Sampling.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
New CleverHans Feature: Better Adversarial Robustness Evaluations with Attack Bundling.
CoRR, 2018

Unrestricted Adversarial Examples.
CoRR, 2018

Skill Rating for Generative Models.
CoRR, 2018

TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing.
CoRR, 2018

Motivating the Rules of the Game for Adversarial Example Research.
CoRR, 2018

Defense Against the Dark Arts: An overview of adversarial example security research and future research directions.
CoRR, 2018

Gradient Masking Causes CLEVER to Overestimate Adversarial Perturbation Size.
CoRR, 2018

Adversarial Attacks and Defences Competition.
CoRR, 2018

Adversarial Logit Pairing.
CoRR, 2018

Adversarial Examples that Fool both Human and Computer Vision.
CoRR, 2018

Making machine learning robust against adversarial inputs.
Commun. ACM, 2018

Realistic Evaluation of Deep Semi-Supervised Learning Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Adversarial Examples that Fool both Computer Vision and Time-Limited Humans.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Sanity Checks for Saliency Maps.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Is Generator Conditioning Causally Related to GAN Performance?
Proceedings of the 35th International Conference on Machine Learning, 2018

Ensemble Adversarial Training: Attacks and Defenses.
Proceedings of the 6th International Conference on Learning Representations, 2018

Realistic Evaluation of Semi-Supervised Learning Algorithms.
Proceedings of the 6th International Conference on Learning Representations, 2018

Adversarial Spheres.
Proceedings of the 6th International Conference on Learning Representations, 2018

Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step.
Proceedings of the 6th International Conference on Learning Representations, 2018

MaskGAN: Better Text Generation via Filling in the _______.
Proceedings of the 6th International Conference on Learning Representations, 2018

Thermometer Encoding: One Hot Way To Resist Adversarial Examples.
Proceedings of the 6th International Conference on Learning Representations, 2018

Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
On the Protection of Private Information in Machine Learning Systems: Two Recent Approaches.
CoRR, 2017

The Space of Transferable Adversarial Examples.
CoRR, 2017

NIPS 2016 Tutorial: Generative Adversarial Networks.
CoRR, 2017

Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data.
Proceedings of the 5th International Conference on Learning Representations, 2017

Adversarial Training Methods for Semi-Supervised Text Classification.
Proceedings of the 5th International Conference on Learning Representations, 2017

Adversarial examples in the physical world.
Proceedings of the 5th International Conference on Learning Representations, 2017

Adversarial Machine Learning at Scale.
Proceedings of the 5th International Conference on Learning Representations, 2017

Adversarial Attacks on Neural Network Policies.
Proceedings of the 5th International Conference on Learning Representations, 2017

On the Protection of Private Information in Machine Learning Systems: Two Recent Approches.
Proceedings of the 30th IEEE Computer Security Foundations Symposium, 2017

Practical Black-Box Attacks against Machine Learning.
Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security, 2017

2016
Practical Black-Box Attacks against Deep Learning Systems using Adversarial Examples.
CoRR, 2016

Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples.
CoRR, 2016

Virtual Adversarial Training for Semi-Supervised Text Classification.
CoRR, 2016

cleverhans v0.1: an adversarial machine learning library.
CoRR, 2016

Net2Net: Accelerating Learning via Knowledge Transfer.
Proceedings of the 4th International Conference on Learning Representations, 2016

Theano: A Python framework for fast computation of mathematical expressions.
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CoRR, 2016

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.
CoRR, 2016

Improved Techniques for Training GANs.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Unsupervised Learning for Physical Interaction through Video Prediction.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Improving the Robustness of Deep Neural Networks via Stability Training.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Deep Learning with Differential Privacy.
Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, 2016

Deep Learning.
Adaptive computation and machine learning, MIT Press, ISBN: 978-0-262-03561-3, 2016

2015
Challenges in representation learning: A report on three machine learning contests.
Neural Networks, 2015

Adversarial Autoencoders.
CoRR, 2015

Qualitatively characterizing neural network optimization problems.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Explaining and Harnessing Adversarial Examples.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Efficient Per-Example Gradient Computations.
CoRR, 2015

On distinguishability criteria for estimating generative models
Proceedings of the 3rd International Conference on Learning Representations, 2015

2014
An empirical analysis of dropout in piecewise linear networks.
Proceedings of the 2nd International Conference on Learning Representations, 2014

Intriguing properties of neural networks.
Proceedings of the 2nd International Conference on Learning Representations, 2014

Generative Adversarial Networks.
CoRR, 2014

An Empirical Investigation of Catastrophic Forgeting in Gradient-Based Neural Networks.
Proceedings of the 2nd International Conference on Learning Representations, 2014

Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks.
Proceedings of the 2nd International Conference on Learning Representations, 2014

Generative Adversarial Nets.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

On the Challenges of Physical Implementations of RBMs.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Scaling Up Spike-and-Slab Models for Unsupervised Feature Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

Piecewise Linear Multilayer Perceptrons and Dropout
CoRR, 2013

Joint Training Deep Boltzmann Machines for Classification
Proceedings of the 1st International Conference on Learning Representations, 2013

Pylearn2: a machine learning research library.
CoRR, 2013

Multi-Prediction Deep Boltzmann Machines.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013


Maxout Networks.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Unsupervised and Transfer Learning Challenge: a Deep Learning Approach.
Proceedings of the Unsupervised and Transfer Learning, 2012

Joint Training of Deep Boltzmann Machines
CoRR, 2012

Theano: new features and speed improvements
CoRR, 2012

Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery
CoRR, 2012

Large-Scale Feature Learning With Spike-and-Slab Sparse Coding.
Proceedings of the 29th International Conference on Machine Learning, 2012

2010
Help me help you: interfaces for personal robots.
Proceedings of the 5th ACM/IEEE International Conference on Human Robot Interaction, 2010

2009
Measuring Invariances in Deep Networks.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009


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