| Improved Training of Wasserstein GANs I Gulrajani, F Ahmed, M Arjovsky, V Dumoulin, AC Courville Advances in Neural Information Processing Systems, 5767-5777, 2017 | 10124 | 2017 |
| Invariant risk minimization M Arjovsky, L Bottou, I Gulrajani, D Lopez-Paz arXiv preprint arXiv:1907.02893, 2019 | 1607 | 2019 |
| Ask me anything: Dynamic memory networks for natural language processing A Kumar, O Irsoy, P Ondruska, M Iyyer, J Bradbury, I Gulrajani, V Zhong, ... International conference on machine learning, 1378-1387, 2016 | 1478 | 2016 |
| In search of lost domain generalization I Gulrajani, D Lopez-Paz arXiv preprint arXiv:2007.01434, 2020 | 820 | 2020 |
| Stanford alpaca: An instruction-following llama model R Taori, I Gulrajani, T Zhang, Y Dubois, X Li, C Guestrin, P Liang, ... | 658 | 2023 |
| SampleRNN: An unconditional end-to-end neural audio generation model S Mehri, K Kumar, I Gulrajani, R Kumar, S Jain, J Sotelo, A Courville, ... arXiv preprint arXiv:1612.07837, 2016 | 639 | 2016 |
| Gansynth: Adversarial neural audio synthesis J Engel, KK Agrawal, S Chen, I Gulrajani, C Donahue, A Roberts arXiv preprint arXiv:1902.08710, 2019 | 462 | 2019 |
| PixelVAE: A Latent Variable Model for Natural Images I Gulrajani, K Kumar, F Ahmed, AA Taiga, F Visin, D Vazquez, A Courville arXiv preprint arXiv:1611.05013, 2016 | 369 | 2016 |
| Diffusion-lm improves controllable text generation X Li, J Thickstun, I Gulrajani, PS Liang, TB Hashimoto Advances in Neural Information Processing Systems 35, 4328-4343, 2022 | 266 | 2022 |
| Alpaca: A strong, replicable instruction-following model R Taori, I Gulrajani, T Zhang, Y Dubois, X Li, C Guestrin, P Liang, ... Stanford Center for Research on Foundation Models. https://crfm. stanford …, 2023 | 121 | 2023 |
| Invariant risk minimization, 2019 M Arjovsky, L Bottou, I Gulrajani, D Lopez-Paz URL http://arxiv. org/abs/1907.02893. cite arxiv 5, 1907 | 56 | 1907 |
| Alpacafarm: A simulation framework for methods that learn from human feedback Y Dubois, X Li, R Taori, T Zhang, I Gulrajani, J Ba, C Guestrin, P Liang, ... arXiv preprint arXiv:2305.14387, 2023 | 55 | 2023 |
| Towards GAN benchmarks which require generalization I Gulrajani, C Raffel, L Metz arXiv preprint arXiv:2001.03653, 2020 | 54 | 2020 |
| SampleRNN: An unconditional end-to-end neural audio generation model (2016) S Mehri, K Kumar, I Gulrajani, R Kumar, S Jain, J Sotelo, A Courville, ... arXiv preprint ArXiv:1612.07837, 2021 | 13 | 2021 |
| Compositional pattern producing GAN L Metz, I Gulrajani NeurIPS Workshops 1, 2017 | 8 | 2017 |
| Likelihood-Based Diffusion Language Models I Gulrajani, TB Hashimoto arXiv preprint arXiv:2305.18619, 2023 | 2 | 2023 |
| Identifiability Conditions for Domain Adaptation I Gulrajani, T Hashimoto International Conference on Machine Learning, 7982-7997, 2022 | 1 | 2022 |
| Evaluating Implicit Generative Models With Large Samples I Gulrajani, C Raffel, L Metz | | 2018 |
Aaron CourvilleProfessor, DIRO, Université de Montréal, Mila, Cifar CAI chairVerified email at umontreal.ca
