| Scaling vision transformers to 22 billion parameters M Dehghani, J Djolonga, B Mustafa, P Padlewski, J Heek, J Gilmer, ... International Conference on Machine Learning, 7480-7512, 2023 | 618 | 2023 |
| Efficiently scaling transformer inference R Pope, S Douglas, A Chowdhery, J Devlin, J Bradbury, J Heek, K Xiao, ... Proceedings of Machine Learning and Systems 5, 606-624, 2023 | 396 | 2023 |
| Metnet: A neural weather model for precipitation forecasting CK Sønderby, L Espeholt, J Heek, M Dehghani, A Oliver, T Salimans, ... arXiv preprint arXiv:2003.12140, 2020 | 325 | 2020 |
| Deep learning for twelve hour precipitation forecasts L Espeholt, S Agrawal, C Sønderby, M Kumar, J Heek, C Bromberg, ... Nature communications 13 (1), 1-10, 2022 | 253 | 2022 |
| simple diffusion: End-to-end diffusion for high resolution images E Hoogeboom, J Heek, T Salimans International Conference on Machine Learning, 13213-13232, 2023 | 247 | 2023 |
| Flax: A neural network library and ecosystem for JAX, 2020 J Heek, A Levskaya, A Oliver, M Ritter, B Rondepierre, A Steiner, ... URL http://github. com/google/flax 1, 2020 | 221 | 2020 |
| Flax: A neural network library and ecosystem for JAX J Heek, A Levskaya, A Oliver, M Ritter, B Rondepierre, A Steiner, ... Version 0.3 3, 14-26, 2020 | 135 | 2020 |
| Patch n’pack: Navit, a vision transformer for any aspect ratio and resolution M Dehghani, B Mustafa, J Djolonga, J Heek, M Minderer, M Caron, ... Advances in Neural Information Processing Systems 36, 2252-2274, 2023 | 90 | 2023 |
| MetNet: A neural weather model for precipitation forecasting C Kaae Sønderby, L Espeholt, J Heek, M Dehghani, A Oliver, T Salimans, ... arXiv e-prints, arXiv: 2003.12140, 2020 | 67 | 2020 |
| Metnet: A neural weather model for precipitation forecasting. arXiv 2020 CK Sønderby, L Espeholt, J Heek, M Dehghani, A Oliver, T Salimans, ... arXiv preprint arXiv:2003.12140, 0 | 53 | |
| Bayesian inference for large scale image classification J Heek, N Kalchbrenner arXiv preprint arXiv:1908.03491, 2019 | 48 | 2019 |
| Imagen 3 J Baldridge, J Bauer, M Bhutani, N Brichtova, A Bunner, L Castrejon, ... arXiv preprint arXiv:2408.07009, 2024 | 28 | 2024 |
| Rolling diffusion models D Ruhe, J Heek, T Salimans, E Hoogeboom arXiv preprint arXiv:2402.09470, 2024 | 25 | 2024 |
| Multistep consistency models J Heek, E Hoogeboom, T Salimans arXiv preprint arXiv:2403.06807, 2024 | 23 | 2024 |
| Multistep distillation of diffusion models via moment matching T Salimans, T Mensink, J Heek, E Hoogeboom Advances in Neural Information Processing Systems 37, 36046-36070, 2024 | 14 | 2024 |
| Skillful twelve hour precipitation forecasts using large context neural networks. arXiv 2021 L Espeholt, S Agrawal, C Sønderby, M Kumar, J Heek, C Bromberg, ... arXiv preprint arXiv:2111.07470, 0 | 11 | |
| Well-calibrated bayesian neural networks J Heek University of Cambridge, 2018 | 7 | 2018 |
| Simpler diffusion (sid2): 1.5 fid on imagenet512 with pixel-space diffusion E Hoogeboom, T Mensink, J Heek, K Lamerigts, R Gao, T Salimans arXiv preprint arXiv:2410.19324, 2024 | 5 | 2024 |
| Robustmix: Improving robustness by regularizing the frequency bias of deep nets J Ngnawe, MA Njifon, J Heek, Y Dauphin arXiv preprint arXiv:2304.02847, 2023 | 4 | 2023 |
| Model Integrity when Unlearning with T2I Diffusion Models A Schioppa, E Hoogeboom, J Heek arXiv preprint arXiv:2411.02068, 2024 | 1 | 2024 |
