| Denoising diffusion implicit models J Song, C Meng, S Ermon International Conference on Learning Representations, 2020 | 3330 | 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 | 972 | 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 | 756 | 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 | 220 | 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 | 189 | 2021 |
| Dual diffusion implicit bridges for image-to-image translation X Su, J Song, C Meng, S Ermon arXiv preprint arXiv:2203.08382, 2022 | 125 | 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 | 110 | 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 | 107 | 2022 |
| 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 | 81 | 2019 |
| Mintnet: Building invertible neural networks with masked convolutions Y Song, C Meng, S Ermon Advances in Neural Information Processing Systems 32, 2019 | 73 | 2019 |
| 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 | 57* | 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 | 48 | 2021 |
| Gaussianization flows C Meng, Y Song, J Song, S Ermon International Conference on Artificial Intelligence and Statistics, 4336-4345, 2020 | 31 | 2020 |
| Density ratio estimation via infinitesimal classification K Choi, C Meng, Y Song, S Ermon International Conference on Artificial Intelligence and Statistics, 2552-2573, 2022 | 27 | 2022 |
| 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 | 26 | 2024 |
| Estimating high order gradients of the data distribution by denoising C Meng, Y Song, W Li, S Ermon Advances in Neural Information Processing Systems 34, 25359-25369, 2021 | 26 | 2021 |
| Accelerating feedforward computation via parallel nonlinear equation solving Y Song, C Meng, R Liao, S Ermon International Conference on Machine Learning, 9791-9800, 2021 | 24* | 2021 |
| Spatial-temporal super-resolution of satellite imagery via conditional pixel synthesis Y He, D Wang, N Lai, W Zhang, C Meng, M Burke, D Lobell, S Ermon Advances in Neural Information Processing Systems 34, 27903-27915, 2021 | 21 | 2021 |
| Efficient spatially sparse inference for conditional gans and diffusion models M Li, J Lin, C Meng, S Ermon, S Han, JY Zhu Advances in Neural Information Processing Systems, 2022 | 19 | 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 | 19 | 2022 |
