| Improved Training of Wasserstein GANs I Gulrajani, F Ahmed, M Arjovsky, V Dumoulin, AC Courville Advances in Neural Information Processing Systems, 5767-5777, 2017 | 12803 | 2017 |
| Invariant risk minimization M Arjovsky, L Bottou, I Gulrajani, D Lopez-Paz arXiv preprint arXiv:1907.02893, 2019 | 2479 | 2019 |
| Stanford alpaca: An instruction-following llama model R Taori, I Gulrajani, T Zhang, Y Dubois, X Li, C Guestrin, P Liang, ... | 2418 | 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 | 1598 | 2016 |
| In search of lost domain generalization I Gulrajani, D Lopez-Paz arXiv preprint arXiv:2007.01434, 2020 | 1313 | 2020 |
| 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 | 757 | 2022 |
| 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 | 747 | 2016 |
| Gansynth: Adversarial neural audio synthesis J Engel, KK Agrawal, S Chen, I Gulrajani, C Donahue, A Roberts arXiv preprint arXiv:1902.08710, 2019 | 586 | 2019 |
| Alpacaeval: An automatic evaluator of instruction-following models X Li, T Zhang, Y Dubois, R Taori, I Gulrajani, C Guestrin, P Liang, ... | 562 | 2023 |
| 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 | 553 | 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, 30039-30069, 2023 | 473 | 2023 |
| 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 | 415 | 2016 |
| Gpt-4o system card A Hurst, A Lerer, AP Goucher, A Perelman, A Ramesh, A Clark, AJ Ostrow, ... arXiv preprint arXiv:2410.21276, 2024 | 310 | 2024 |
| Stanford alpaca: an instruction-following llama model (2023) R Taori, I Gulrajani, T Zhang, Y Dubois, X Li, C Guestrin, P Liang, ... | 145 | 2023 |
| Invariant risk minimization. arXiv 2019 M Arjovsky, L Bottou, I Gulrajani, D Lopez-Paz arXiv preprint arXiv:1907.02893, 1907 | 94 | 1907 |
| Towards GAN benchmarks which require generalization I Gulrajani, C Raffel, L Metz arXiv preprint arXiv:2001.03653, 2020 | 67 | 2020 |
| Likelihood-based diffusion language models I Gulrajani, TB Hashimoto Advances in Neural Information Processing Systems 36, 16693-16715, 2023 | 44 | 2023 |
| 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 | 11 | 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 | 4 | 2022 |
Aaron CourvilleProfessor, DIRO, Université de Montréal, Mila, Cifar CAI chair在 umontreal.ca 的電子郵件地址已通過驗證