Carlos Fernandez-Granda | DeepAI

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Featured Co-authors

Yue Wu
122 publications
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105 publications
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76 publications
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41 publications
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∙ 12/23/2022

Principled and Efficient Transfer Learning of Deep Models via Neural Collapse

With the ever-growing model size and the limited availability of labeled...

0 Xiao Li, et al. ∙

∙ 12/02/2022

Avoiding spurious correlations via logit correction

Empirical studies suggest that machine learning models trained with empi...

10 Sheng Liu, et al. ∙

∙ 10/11/2022

Evaluating Unsupervised Denoising Requires Unsupervised Metrics

Unsupervised denoising is a crucial challenge in real-world imaging appl...

0 Adria Marcos-Morales, et al. ∙

∙ 12/21/2021

PrimSeq: a deep learning-based pipeline to quantitate rehabilitation training

Stroke rehabilitation seeks to increase neuroplasticity through the repe...

18 Avinash Parnandi, et al. ∙

∙ 11/03/2021

Sequence-to-Sequence Modeling for Action Identification at High Temporal Resolution

Automatic action identification from video and kinematic data is an impo...

0 Aakash Kaku, et al. ∙

∙ 10/07/2021

Adaptive Early-Learning Correction for Segmentation from Noisy Annotations

Deep learning in the presence of noisy annotations has been studied exte...

0 Sheng Liu, et al. ∙

∙ 09/22/2021

Cramér-Rao bound-informed training of neural networks for quantitative MRI

Neural networks are increasingly used to estimate parameters in quantita...

10 Xiaoxia Zhang, et al. ∙

∙ 07/27/2021

Adaptive Denoising via GainTuning

Deep convolutional neural networks (CNNs) for image denoising are usuall...

2 Sreyas Mohan, et al. ∙

∙ 06/13/2021

Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis

In the last few years, deep learning classifiers have shown promising re...

13 Kangning Liu, et al. ∙

∙ 03/01/2021

Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training

Normalization techniques have become a basic component in modern convolu...

13 Sheng Liu, et al. ∙

∙ 11/30/2020

Unsupervised Deep Video Denoising

Deep convolutional neural networks (CNNs) currently achieve state-of-the...

8 Dev Yashpal Sheth, et al. ∙

∙ 10/24/2020

Deep Denoising For Scientific Discovery: A Case Study In Electron Microscopy

Denoising is a fundamental challenge in scientific imaging. Deep convolu...

11 Sreyas Mohan, et al. ∙

∙ 08/04/2020

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department

During the COVID-19 pandemic, rapid and accurate triage of patients at t...

71 Farah E Shamout, et al. ∙

∙ 06/30/2020

Early-Learning Regularization Prevents Memorization of Noisy Labels

We propose a novel framework to perform classification via deep learning...

0 Sheng Liu, et al. ∙

∙ 04/14/2020

Towards data-driven stroke rehabilitation via wearable sensors and deep learning

Recovery after stroke is often incomplete, but rehabilitation training m...

3 Aakash Kaku, et al. ∙

∙ 03/30/2020

A Sampling Theorem for Deconvolution in Two Dimensions

This work studies the problem of estimating a two-dimensional superposit...

0 Joseph McDonald, et al. ∙

∙ 02/10/2020

Be Like Water: Robustness to Extraneous Variables Via Adaptive Feature Normalization

Extraneous variables are variables that are irrelevant for a certain tas...

4 Aakash Kaku, et al. ∙

∙ 11/09/2019

On the design of convolutional neural networks for automatic detection of Alzheimer's disease

Early detection is a crucial goal in the study of Alzheimer's Disease (A...

21 Sheng Liu, et al. ∙

∙ 06/13/2019

Robust and interpretable blind image denoising via bias-free convolutional neural networks

Deep convolutional networks often append additive constant ("bias") term...

6 Sreyas Mohan, et al. ∙

∙ 06/03/2019

Data-driven Estimation of Sinusoid Frequencies

Frequency estimation is a fundamental problem in signal processing, with...

0 Gautier Izacard, et al. ∙

∙ 05/12/2019

Sparse Recovery Beyond Compressed Sensing: Separable Nonlinear Inverse Problems

Extracting information from nonlinear measurements is a fundamental chal...

0 Brett Bernstein, et al. ∙

∙ 04/09/2019

Time-Series Analysis via Low-Rank Matrix Factorization: Applied to Infant-Sleep Data

We propose a nonparametric model for time series with missing data based...

0 Sheng Liu, et al. ∙

∙ 11/14/2018

A Learning-Based Framework for Line-Spectra Super-resolution

We propose a learning-based approach for estimating the spectrum of a mu...

0 Gautier Izacard, et al. ∙

∙ 02/28/2018

Multicompartment Magnetic Resonance Fingerprinting

Magnetic resonance fingerprinting (MRF) is a technique for quantitative ...

0 Sunli Tang, et al. ∙

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