Carlos Fernandez-Granda

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Sheng LiuStanford UniversityEmail yang diverifikasi di stanford.edu
Narges RazavianNew York University Medical CenterEmail yang diverifikasi di nyumc.org
Sreyas MohanMetaEmail yang diverifikasi di nyu.edu
Peter A CrozierArizona State UniversityEmail yang diverifikasi di asu.edu
Joshua L. VincentArizona State UniversityEmail yang diverifikasi di asu.edu
Aakash KakuGoogle, PhD @ NYUEmail yang diverifikasi di google.com
Eero P SimoncelliProfessor of Neural Science, Mathematics, Data Science, Psychology @ NYU.Email yang diverifikasi di nyu.edu
Emmanuel CandesThe Simons Chair in Mathematics and Statistics, Stanford UniversityEmail yang diverifikasi di stanford.edu
Weicheng ZhuCenter for Data Science, New York UniversityEmail yang diverifikasi di nyu.edu
Kangning LiuAdobe IncEmail yang diverifikasi di adobe.com
Yiqiu ShenNew York UniversityEmail yang diverifikasi di nyu.edu
Krzysztof J. GerasNew York UniversityEmail yang diverifikasi di nyu.edu
Dev Yashpal ShethIndian Institute of Technology MadrasEmail yang diverifikasi di cse.iitm.ac.in
Brett BernsteinNew York UniversityEmail yang diverifikasi di cims.nyu.edu
Jonathan Niles-WeedNew York UniversityEmail yang diverifikasi di cims.nyu.edu
David S. MattesonProfessor, Statistics & Data Science, Cornell UniversityEmail yang diverifikasi di cornell.edu
Avinash ParnandiVitalConnectEmail yang diverifikasi di nyulangone.org
Heidi SchambraNYU Grossman School of MedicineEmail yang diverifikasi di nyumc.org
Jakob AssländerNew York University School of MedicineEmail yang diverifikasi di nyumc.org
Nan WuNew York University, Center for Data ScienceEmail yang diverifikasi di nyu.edu

Ikuti

Carlos Fernandez-Granda

Courant Institute and Center for Data Science, New York University

Email yang diverifikasi di cims.nyu.edu - Beranda

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


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
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	1420	2024
Towards a mathematical theory of super‐resolution EJ Candès, C Fernandez‐Granda Communications on pure and applied Mathematics 67 (6), 906-956, 2014	1399	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	661	2020
Super-resolution from noisy data EJ Candès, C Fernandez-Granda Journal of Fourier Analysis and Applications 19, 1229-1254, 2013	476	2013
Super-resolution of point sources via convex programming C Fernandez-Granda Information and Inference 5 (3), 251-303, 2016	157	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	154	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	130	2022
Support detection in super-resolution C Fernandez-Granda Proceedings of the 10th International Conference on Sampling Theory and …, 2013	119	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
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	74	2021
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	74	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	73	2013
Data-driven Estimation of Sinusoid Frequencies G Izacard, S Mohan, C Fernandez-Granda Proceedings of the 33rd Conference on Neural Information Processing Systems …, 2019	67	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	65	2023
Multicompartment Magnetic Resonance Fingerprinting S Tang, C Fernandez-Granda, S Lannuzel, B Bernstein, R Lattanzi, ... Inverse Problems 34 (9), 2018	50	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	48	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	45	2022
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
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	41	2021

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