Carlos Fernandez-Granda
Carlos Fernandez-Granda
Courant Institute and Center for Data Science, New York University
Verified email at - Homepage
Cited by
Cited by
Towards a mathematical theory of super‐resolution
EJ Candès, C Fernandez‐Granda
Communications on pure and applied Mathematics 67 (6), 906-956, 2014
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
Super-resolution from noisy data
EJ Candès, C Fernandez-Granda
Journal of Fourier Analysis and Applications 19, 1229-1254, 2013
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
Super-resolution of point sources via convex programming
C Fernandez-Granda
Information and Inference 5 (3), 251-303, 2016
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 Jastrzêbski, ...
NPJ digital medicine 4 (1), 80, 2021
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
Support detection in super-resolution
C Fernandez-Granda
Proceedings of the 10th International Conference on Sampling Theory and …, 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
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
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
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
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
Data-driven Estimation of Sinusoid Frequencies
G Izacard, S Mohan, C Fernandez-Granda
Proceedings of the 33rd Conference on Neural Information Processing Systems …, 2019
Multicompartment Magnetic Resonance Fingerprinting
S Tang, C Fernandez-Granda, S Lannuzel, B Bernstein, R Lattanzi, ...
Inverse Problems 34 (9), 2018
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
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
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
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
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
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