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Christopher Olah

I do basic research in deep learning. I try to understand the inner workings of neural networks, among other projects. I also spend a lot of time thinking about how to explain them.

I believe strongly that my job as a researcher is to advance and serve the field, and the public broadly. I believe that I often serve the field better by writing in media other than the traditional academic paper.

Instead, I mostly write online essays. Some of these are tutorials on important ideas in the field, while others present novel research.

Google Publications

Changing Model Behavior at Test-time using Reinforcement Learning

Augustus Odena, Dieterich Lawson, Chris Olah

ICLR Workshop (2017)
Conditional Image Synthesis With Auxiliary Classifier GANs

Augustus Odena, Christopher Olah, Jonathon Shlens

ICML (2017)
Concrete Problems in AI Safety

Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman, Dan Mané

arXiv preprint arXiv:1606.06565 (2016)
Deconvolution and Checkerboard Artifacts

Augustus Odena, Vincent Dumoulin, Chris Olah

Distill (2016)
Experiments in Handwriting with a Neural Network

Shan Carter, David Ha, Ian Johnson, Christopher Olah

Distill (2016)
Experiments in Handwriting with a Neural Network

Shan Carter, David Ha, Ian Johnson, Chris Olah

Distill (2016)
Calculus on Computational Graphs: Backpropagation

Christopher Olah

colah.github.io (2015)
Document embedding with paragraph vectors

Andrew M. Dai, Christopher Olah, Quoc V. Le

NIPS Deep Learning Workshop (2015)
Inceptionism: Going Deeper into Neural Networks

Alexander Mordvintsev, Christopher Olah, Mike Tyka

Google Research Blog (2015)
Neural Networks, Types, and Functional Programming

Christopher Olah

colah.github.io (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)
Understanding LSTM Networks

Christopher Olah

colah.github.io (2015)
Visual Information Theory

Christopher Olah

colah.github.io (2015)

Previous Publications

Conv Nets: A Modular Perspective

Christopher Olah

colah.github.io (2014)
Deep Learning, NLP, and Representations

Christopher Olah

colah.github.io (2014)
Groups & Group Convolutions

Christopher Olah

colah.github.io (2014)
Neural Networks, Manifolds, and Topology

Christopher Olah

colah.github.io (2014)
Understanding Convolutions

Christopher Olah

colah.github.io (2014)
Visualizing MNIST: An Exploration of Dimensionality Reduction

Christopher Olah

colah.github.io (2014)
Visualizing Representations: Deep Learning and Human Beings

Christopher Olah

colah.github.io (2014)