Carlos Fernandez-Granda

Citado por

	Total	Desde 2020
Citas	5576	4214
Índice h	26	24
Índice i10	35	35

1900

950

475

1425

201320142015201620172018201920202021202220232024202561 111 186 214 264 252 242 265 383 581 807 1840 317

Acceso público

Ver todo

44 artículos

1 artículo

disponibles

no disponibles

Basado en requisitos de financiación

Coautores

Sheng LiuStanford UniversityDirección de correo verificada de stanford.edu
Narges RazavianNew York University Medical CenterDirección de correo verificada de nyumc.org
Sreyas MohanMetaDirección de correo verificada de nyu.edu
Peter A CrozierArizona State UniversityDirección de correo verificada de asu.edu
Joshua L. VincentArizona State UniversityDirección de correo verificada de asu.edu
Aakash KakuGoogle, PhD @ NYUDirección de correo verificada de google.com
Eero P SimoncelliProfessor of Neural Science, Mathematics, Data Science, Psychology @ NYU.Dirección de correo verificada de nyu.edu
Emmanuel CandesThe Simons Chair in Mathematics and Statistics, Stanford UniversityDirección de correo verificada de stanford.edu
Weicheng ZhuCenter for Data Science, New York UniversityDirección de correo verificada de nyu.edu
Kangning LiuAdobe IncDirección de correo verificada de adobe.com
Yiqiu ShenNew York UniversityDirección de correo verificada de nyu.edu
Krzysztof J. GerasNew York UniversityDirección de correo verificada de nyu.edu
Dev Yashpal ShethIndian Institute of Technology MadrasDirección de correo verificada de cse.iitm.ac.in
Brett BernsteinNew York UniversityDirección de correo verificada de cims.nyu.edu
Jonathan Niles-WeedNew York UniversityDirección de correo verificada de cims.nyu.edu
Avinash ParnandiVitalConnectDirección de correo verificada de nyulangone.org
Heidi SchambraNYU Grossman School of MedicineDirección de correo verificada de nyumc.org
Jakob AssländerNew York University School of MedicineDirección de correo verificada de nyumc.org
Nan WuNew York University, Center for Data ScienceDirección de correo verificada de nyu.edu
David S. MattesonProfessor, Statistics & Data Science, Cornell UniversityDirección de correo verificada de cornell.edu

Seguir

Carlos Fernandez-Granda

Courant Institute and Center for Data Science, New York University

Dirección de correo verificada de cims.nyu.edu - Página principal

machine learning image processing data-driven medicine signal processing inverse problems


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Towards a mathematical theory of super‐resolution EJ Candès, C Fernandez‐Granda Communications on pure and applied Mathematics 67 (6), 906-956, 2014	1386	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	1228	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	649	2020
Super-resolution from noisy data EJ Candès, C Fernandez-Granda Journal of Fourier Analysis and Applications 19, 1229-1254, 2013	472	2013
Super-resolution of point sources via convex programming C Fernandez-Granda Information and Inference 5 (3), 251-303, 2016	156	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	152	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	145	2021
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	124	2022
Support detection in super-resolution C Fernandez-Granda Proceedings of the 10th International Conference on Sampling Theory and …, 2013	118	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	110	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	75	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	74	2013
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	72	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	64	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	63	2023
Multicompartment Magnetic Resonance Fingerprinting S Tang, C Fernandez-Granda, S Lannuzel, B Bernstein, R Lattanzi, ... Inverse Problems 34 (9), 2018	49	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	45	2019
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
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	42	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

El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.

Artículos 1–20

Citas por año

Citas duplicadas

Citas combinadas

Añadir coautoresCoautores

Seguir

Citado por

Coautores