Hi! I'm a PhD student at Stanford studying machine learning. Previously I've worked at Facebook AI Research, Google Brain, and Mila.
I'm interested in principled approaches to out-of-distribution generalization, causal inference, and unsupervised learning.
Outside of work, I perform improv comedy (poorly) and play the piano (even moreso).
Email: igul222 at gmail.com
Invariant Risk Minimization
Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, David Lopez-Paz. arXiv preprint.
Towards GAN Benchmarks Which Require Generalization
Ishaan Gulrajani, Colin Raffel, Luke Metz. ICLR 2019.
GANSynth: Adversarial Neural Audio Synthesis
Jesse Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani, Chris Donahue, Adam Roberts. ICLR 2019.
Improved Training of Wasserstein GANs
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, Aaron Courville. NIPS 2017.
PixelVAE: A Latent Variable Model for Natural Images
Ishaan Gulrajani, Kundan Kumar, Faruk Ahmed, Adrien Ali Taiga, Francesco Visin, David Vazquez, Aaron Courville. ICLR 2017.
SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
Soroush Mehri, Kundan Kumar, Ishaan Gulrajani, Rithesh Kumar, Shubham Jain, Jose Sotelo, Aaron Courville, Yoshua Bengio. ICLR 2017.
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing
Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, Richard Socher. ICML 2016.