| Towards a mathematical theory of super‐resolution EJ Candès, C Fernandez‐Granda Communications on pure and applied Mathematics 67 (6), 906-956, 2014 | 1375 | 2014 |
| Dictionary learning for integrative, multimodal and scalable single-cell analysis Y Hao, T Stuart, MH Kowalski, S Choudhary, P Hoffman, A Hartman, ... Nature biotechnology 42 (2), 293-304, 2024 | 897 | 2024 |
| Early-learning regularization prevents memorization of noisy labels S Liu, J Niles-Weed, N Razavian, C Fernandez-Granda Proceedings of the 34th Conference on Neural Information Processing Systems …, 2020 | 614 | 2020 |
| Super-resolution from noisy data EJ Candès, C Fernandez-Granda Journal of Fourier Analysis and Applications 19, 1229-1254, 2013 | 467 | 2013 |
| Super-resolution of point sources via convex programming C Fernandez-Granda Information and Inference 5 (3), 251-303, 2016 | 155 | 2016 |
| Robust and interpretable blind image denoising via bias-free convolutional neural networks S Mohan, Z Kadkhodaie, EP Simoncelli, C Fernandez-Granda Proceedings of the International Conference on Learning Representations (ICLR), 2019 | 146 | 2019 |
| An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department FE Shamout, Y Shen, N Wu, A Kaku, J Park, T Makino, S Jastrzębski, ... NPJ digital medicine 4 (1), 80, 2021 | 140 | 2021 |
| Support detection in super-resolution C Fernandez-Granda Proceedings of the 10th International Conference on Sampling Theory and …, 2013 | 116 | 2013 |
| Adaptive early-learning correction for segmentation from noisy annotations S Liu, K Liu, W Zhu, Y Shen, C Fernandez-Granda Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 112 | 2022 |
| Generalizable deep learning model for early Alzheimer’s disease detection from structural MRIs S Liu, AV Masurkar, H Rusinek, J Chen, B Zhang, W Zhu, ... Scientific reports 12 (1), 17106, 2022 | 87 | 2022 |
| Super-resolution via transform-invariant group-sparse regularization C Fernandez-Granda, EJ Candes Proceedings of the IEEE international conference on computer vision, 3336-3343, 2013 | 74 | 2013 |
| On the design of convolutional neural networks for automatic detection of Alzheimer's disease S Liu, C Yadav, C Fernandez-Granda, N Razavian Proceedings of Machine Learning Research, NeurIPS Machine Learning for …, 2019 | 73 | 2019 |
| Unsupervised deep video denoising DY Sheth, S Mohan, JL Vincent, R Manzorro, PA Crozier, MM Khapra, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 67 | 2021 |
| Data-driven Estimation of Sinusoid Frequencies G Izacard, S Mohan, C Fernandez-Granda Proceedings of the 33rd Conference on Neural Information Processing Systems …, 2019 | 61 | 2019 |
| Benchmarking of machine learning ocean subgrid parameterizations in an idealized model A Ross, Z Li, P Perezhogin, C Fernandez‐Granda, L Zanna Journal of Advances in Modeling Earth Systems 15 (1), 2023 | 58 | 2023 |
| Multicompartment Magnetic Resonance Fingerprinting S Tang, C Fernandez-Granda, S Lannuzel, B Bernstein, R Lattanzi, ... Inverse Problems 34 (9), 2018 | 48 | 2018 |
| Demixing sines and spikes: Robust spectral super-resolution in the presence of outliers C Fernandez-Granda, G Tang, X Wang, L Zheng Information and Inference: A Journal of the IMA 7 (1), 105-168, 2018 | 43 | 2018 |
| A Learning-Based Framework for Line-Spectra Super-resolution G Izacard, B Bernstein, C Fernandez-Granda International Conference on Acoustics, Speech, and Signal Processing, 2019 | 42 | 2019 |
| Deep denoising for scientific discovery: A case study in electron microscopy S Mohan, R Manzorro, JL Vincent, B Tang, DY Sheth, EP Simoncelli, ... IEEE Transactions on Computational Imaging 8, 585-597, 2022 | 40 | 2022 |
| Developing and evaluating deep neural network-based denoising for nanoparticle TEM images with ultra-low signal-to-noise JL Vincent, R Manzorro, S Mohan, B Tang, DY Sheth, EP Simoncelli, ... Microscopy and Microanalysis 27 (6), 1431-1447, 2021 | 39 | 2021 |
Sheng LiuStanford UniversityVerified email at stanford.edu
