| Denoising diffusion implicit models J Song, C Meng, S Ermon International Conference on Learning Representations, 2020 | 5637 | 2020 |
| Sdedit: Guided image synthesis and editing with stochastic differential equations C Meng, Y He, Y Song, J Song, J Wu, JY Zhu, S Ermon arXiv preprint arXiv:2108.01073, 2021 | 1471 | 2021 |
| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 1144 | 2022 |
| On distillation of guided diffusion models C Meng, R Rombach, R Gao, D Kingma, S Ermon, J Ho, T Salimans Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 377 | 2023 |
| Geography-aware self-supervised learning K Ayush, B Uzkent, C Meng, K Tanmay, M Burke, D Lobell, S Ermon Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 236 | 2021 |
| Satmae: Pre-training transformers for temporal and multi-spectral satellite imagery Y Cong, S Khanna, C Meng, P Liu, E Rozi, Y He, M Burke, DB Lobell, ... Advances in Neural Information Processing Systems, 2022 | 199 | 2022 |
| Dual diffusion implicit bridges for image-to-image translation X Su, J Song, C Meng, S Ermon arXiv preprint arXiv:2203.08382, 2022 | 182 | 2022 |
| D2c: Diffusion-decoding models for few-shot conditional generation A Sinha, J Song, C Meng, S Ermon Advances in Neural Information Processing Systems 34, 12533-12548, 2021 | 141 | 2021 |
| Holistic evaluation of text-to-image models T Lee, M Yasunaga, C Meng, Y Mai, JS Park, A Gupta, Y Zhang, ... Advances in Neural Information Processing Systems 36, 2024 | 96 | 2024 |
| Predicting economic development using geolocated wikipedia articles E Sheehan, C Meng, M Tan, B Uzkent, N Jean, M Burke, D Lobell, ... Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019 | 91 | 2019 |
| Mintnet: Building invertible neural networks with masked convolutions Y Song, C Meng, S Ermon Advances in Neural Information Processing Systems 32, 2019 | 82 | 2019 |
| Denoising diffusion implicit models (2020) J Song, C Meng, S Ermon arXiv preprint arXiv:2010.02502, 2010 | 71 | 2010 |
| Mastering text-to-image diffusion: Recaptioning, planning, and generating with multimodal llms L Yang, Z Yu, C Meng, M Xu, S Ermon, CUI Bin Forty-first International Conference on Machine Learning, 2024 | 61 | 2024 |
| Learning to interpret satellite images using wikipedia B Uzkent, E Sheehan, C Meng, Z Tang, M Burke, D Lobell, S Ermon Proceedings of the Twenty-Eighth International Joint Conference on …, 2019 | 61* | 2019 |
| Sustainbench: Benchmarks for monitoring the sustainable development goals with machine learning C Yeh, C Meng, S Wang, A Driscoll, E Rozi, P Liu, J Lee, M Burke, ... Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021 | 58 | 2021 |
| Density ratio estimation via infinitesimal classification K Choi, C Meng, Y Song, S Ermon International Conference on Artificial Intelligence and Statistics, 2552-2573, 2022 | 43 | 2022 |
| Concrete Score Matching: Generalized Score Matching for Discrete Data C Meng, K Choi, J Song, S Ermon Advances in Neural Information Processing Systems, 2022 | 40 | 2022 |
| Gaussianization flows C Meng, Y Song, J Song, S Ermon International Conference on Artificial Intelligence and Statistics, 4336-4345, 2020 | 38 | 2020 |
| Diffusionsat: A generative foundation model for satellite imagery S Khanna, P Liu, L Zhou, C Meng, R Rombach, M Burke, D Lobell, ... arXiv preprint arXiv:2312.03606, 2023 | 37 | 2023 |
| Discrete diffusion language modeling by estimating the ratios of the data distribution A Lou, C Meng, S Ermon | 37 | 2023 |
