| Improved Training of Wasserstein GANs I Gulrajani, F Ahmed, M Arjovsky, V Dumoulin, AC Courville Advances in Neural Information Processing Systems, 5767-5777, 2017 | 11909 | 2017 |
| Invariant risk minimization M Arjovsky, L Bottou, I Gulrajani, D Lopez-Paz arXiv preprint arXiv:1907.02893, 2019 | 2169 | 2019 |
| Stanford alpaca: An instruction-following llama model R Taori, I Gulrajani, T Zhang, Y Dubois, X Li, C Guestrin, P Liang, ... | 1879 | 2023 |
| 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 | 1563 | 2016 |
| In search of lost domain generalization I Gulrajani, D Lopez-Paz arXiv preprint arXiv:2007.01434, 2020 | 1157 | 2020 |
| 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 | 714 | 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 | 591 | 2022 |
| Gansynth: Adversarial neural audio synthesis J Engel, KK Agrawal, S Chen, I Gulrajani, C Donahue, A Roberts arXiv preprint arXiv:1902.08710, 2019 | 544 | 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 | 401 | 2016 |
| 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 | 391 | 2023 |
| Alpacaeval: An automatic evaluator of instruction-following models X Li, T Zhang, Y Dubois, R Taori, I Gulrajani, C Guestrin, P Liang, ... | 337 | 2023 |
| Alpacafarm: A simulation framework for methods that learn from human feedback Y Dubois, CX Li, R Taori, T Zhang, I Gulrajani, J Ba, C Guestrin, PS Liang, ... Advances in Neural Information Processing Systems 36, 2024 | 295 | 2024 |
| Stanford alpaca: an instruction-following llama model (2023) R Taori, I Gulrajani, T Zhang, Y Dubois, X Li, C Guestrin, P Liang, ... URL https://github. com/tatsu-lab/stanford_alpaca 1 (9), 2023 | 94 | 2023 |
| Invariant risk minimization. arXiv 2019 M Arjovsky, L Bottou, I Gulrajani, D Lopez-Paz arXiv preprint arXiv:1907.02893, 1907 | 79 | 1907 |
| Towards GAN benchmarks which require generalization I Gulrajani, C Raffel, L Metz arXiv preprint arXiv:2001.03653, 2020 | 63 | 2020 |
| Likelihood-based diffusion language models I Gulrajani, TB Hashimoto Advances in Neural Information Processing Systems 36, 2024 | 20 | 2024 |
| 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 | 15 | 2021 |
| Compositional pattern producing GAN L Metz, I Gulrajani NeurIPS Workshops 1, 2017 | 8 | 2017 |
| Identifiability conditions for domain adaptation I Gulrajani, T Hashimoto International Conference on Machine Learning, 7982-7997, 2022 | 3 | 2022 |
| Evaluating Implicit Generative Models With Large Samples I Gulrajani, C Raffel, L Metz | | |
Aaron CourvilleProfessor, DIRO, Université de Montréal, Mila, Cifar CAI chairVerified email at umontreal.ca
