Carlos Fernandez-Granda

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 59

Top Topics

Convolutional Neural Networks

Sampling Theorem

Supervised Learning

Top Venues

npj Digit. Medicine

Publications

Yanqi Xu, Yiqiu Shen, Carlos Fernandez-Granda, Laura Heacock, Krzysztof J. Geras
Understanding differences in applying DETR to natural and medical images. CoRR (2024)
Boyang Yu, Aakash Kaku, Kangning Liu, Avinash Parnandi, Emily Fokas, Anita Venkatesan, Natasha Pandit, Rajesh Ranganath, Heidi M. Schambra, Carlos Fernandez-Granda
Quantifying impairment and disease severity using AI models trained on healthy subjects. npj Digit. Medicine 7 (1) (2024)
Xiao Li, Sheng Liu, Jinxin Zhou, Xinyu Lu, Carlos Fernandez-Granda, Zhihui Zhu, Qing Qu
Understanding and Improving Transfer Learning of Deep Models via Neural Collapse. Trans. Mach. Learn. Res. 2024 (2024)
Weicheng Zhu, Sheng Liu, Carlos Fernandez-Granda, Narges Razavian
Making Self-supervised Learning Robust to Spurious Correlation via Learning-speed Aware Sampling. CoRR (2023)
Boyang Yu, Aakash Kaku, Kangning Liu, Avinash Parnandi, Emily Fokas, Anita Venkatesan, Natasha Pandit, Rajesh Ranganath, Heidi M. Schambra, Carlos Fernandez-Granda
Quantifying Impairment and Disease Severity Using AI Models Trained on Healthy Subjects. CoRR (2023)
Sheng Liu, Xu Zhang, Nitesh Sekhar, Yue Wu, Prateek Singhal, Carlos Fernandez-Granda
Avoiding spurious correlations via logit correction. ICLR (2023)
Adria Marcos-Morales, Matan Leibovich, Sreyas Mohan, Joshua Lawrence Vincent, Piyush Haluai, Mai Tan, Peter A. Crozier, Carlos Fernandez-Granda
Evaluating Unsupervised Denoising Requires Unsupervised Metrics. ICML (2023)
Kangning Liu, Weicheng Zhu, Yiqiu Shen, Sheng Liu, Narges Razavian, Krzysztof J. Geras, Carlos Fernandez-Granda
Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning. CVPR (2023)
Weicheng Zhu, Carlos Fernandez-Granda, Narges Razavian
Interpretable Prediction of Lung Squamous Cell Carcinoma Recurrence With Self-supervised Learning. CoRR (2022)
Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi M. Schambra, Carlos Fernandez-Granda
StrokeRehab: A Benchmark Dataset for Sub-second Action Identification. NeurIPS (2022)
Sheng Liu, Xu Zhang, Nitesh Sekhar, Yue Wu, Prateek Singhal, Carlos Fernandez-Granda
Avoiding spurious correlations via logit correction. CoRR (2022)
Adria Marcos-Morales, Matan Leibovich, Sreyas Mohan, Joshua Lawrence Vincent, Piyush Haluai, Mai Tan, Peter A. Crozier, Carlos Fernandez-Granda
Evaluating Unsupervised Denoising Requires Unsupervised Metrics. CoRR (2022)
Sheng Liu, Kangning Liu, Weicheng Zhu, Yiqiu Shen, Carlos Fernandez-Granda
Adaptive Early-Learning Correction for Segmentation from Noisy Annotations. CVPR (2022)
Pau Batlle, Joan Bruna, Carlos Fernandez-Granda, Victor M. Preciado
Adaptive Test Allocation for Outbreak Detection and Tracking in Social Contact Networks. SIAM J. Control. Optim. 60 (2) (2022)
Xiao Li, Sheng Liu, Jinxin Zhou, Xinyu Lu, Carlos Fernandez-Granda, Zhihui Zhu, Qing Qu
Principled and Efficient Transfer Learning of Deep Models via Neural Collapse. CoRR (2022)
Kangning Liu, Weicheng Zhu, Yiqiu Shen, Sheng Liu, Narges Razavian, Krzysztof J. Geras, Carlos Fernandez-Granda
Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning. CoRR (2022)
Sreyas Mohan, Ramon Manzorro, Joshua L. Vincent, Binh Tang, Dev Yashpal Sheth, Eero P. Simoncelli, David S. Matteson, Peter A. Crozier, Carlos Fernandez-Granda
Deep Denoising for Scientific Discovery: A Case Study in Electron Microscopy. IEEE Trans. Computational Imaging 8 (2022)
Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Haoxiang Huang, Laure Zanna, Narges Razavian, Jonathan Niles-Weed, Carlos Fernandez-Granda
Deep Probability Estimation. ICML (2022)
Weicheng Zhu, Carlos Fernandez-Granda, Narges Razavian
Interpretable Prediction of Lung Squamous Cell Carcinoma Recurrence With Self-supervised Learning. MIDL (2022)
Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. NeurIPS (2021)
Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanislaw Jastrzebski, Jan Witowski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. npj Digit. Medicine 4 (2021)
Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. CoRR (2021)
Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Laure Zanna, Narges Razavian, Carlos Fernandez-Granda
Deep Probability Estimation. CoRR (2021)
Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi M. Schambra, Carlos Fernandez-Granda
Sequence-to-Sequence Modeling for Action Identification at High Temporal Resolution. CoRR (2021)
Avinash Parnandi, Aakash Kaku, Anita Venkatesan, Natasha Pandit, Audre Wirtanen, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Dawn Nilsen, Carlos Fernandez-Granda, Heidi M. Schambra
PrimSeq: a deep learning-based pipeline to quantitate rehabilitation training. CoRR (2021)
Dev Yashpal Sheth, Sreyas Mohan, Joshua L. Vincent, Ramon Manzorro, Peter A. Crozier, Mitesh M. Khapra, Eero P. Simoncelli, Carlos Fernandez-Granda
Unsupervised Deep Video Denoising. ICCV (2021)
Kangning Liu, Yiqiu Shen, Nan Wu, Jakub Piotr Chledowski, Carlos Fernandez-Granda, Krzysztof J. Geras
Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis. MIDL (2021)
Xiaoxia Zhang, Quentin Duchemin, Kangning Liu, Sebastian Flassbeck, Cem Gultekin, Carlos Fernandez-Granda, Jakob Assländer
Cramér-Rao bound-informed training of neural networks for quantitative MRI. CoRR (2021)
Kangning Liu, Yiqiu Shen, Nan Wu, Jakub Chledowski, Carlos Fernandez-Granda, Krzysztof J. Geras
Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis. CoRR (2021)
Sreyas Mohan, Joshua L. Vincent, Ramon Manzorro, Peter A. Crozier, Eero P. Simoncelli, Carlos Fernandez-Granda
Adaptive Denoising via GainTuning. CoRR (2021)
Sreyas Mohan, Joshua L. Vincent, Ramon Manzorro, Peter A. Crozier, Carlos Fernandez-Granda, Eero P. Simoncelli
Adaptive Denoising via GainTuning. NeurIPS (2021)
Sheng Liu, Kangning Liu, Weicheng Zhu, Yiqiu Shen, Carlos Fernandez-Granda
Adaptive Early-Learning Correction for Segmentation from Noisy Annotations. CoRR (2021)
Aakash Kaku, Sreyas Mohan, Avinash Parnandi, Heidi M. Schambra, Carlos Fernandez-Granda
Be Like Water: Robustness to Extraneous Variables Via Adaptive Feature Normalization. CoRR (2020)
Aakash Kaku, Avinash Parnandi, Anita Venkatesan, Natasha Pandit, Heidi M. Schambra, Carlos Fernandez-Granda
Towards data-driven stroke rehabilitation via wearable sensors and deep learning. CoRR (2020)
Brett Bernstein, Sheng Liu, Chrysa Papadaniil, Carlos Fernandez-Granda
Sparse Recovery Beyond Compressed Sensing: Separable Nonlinear Inverse Problems. IEEE Trans. Inf. Theory 66 (9) (2020)
Sheng Liu, Jonathan Niles-Weed, Narges Razavian, Carlos Fernandez-Granda
Early-Learning Regularization Prevents Memorization of Noisy Labels. NeurIPS (2020)
Sreyas Mohan, Ramon Manzorro, Joshua L. Vincent, Binh Tang, Dev Yashpal Sheth, Eero P. Simoncelli, David S. Matteson, Peter A. Crozier, Carlos Fernandez-Granda
Deep Denoising For Scientific Discovery: A Case Study In Electron Microscopy. CoRR (2020)
Aakash Kaku, Avinash Parnandi, Anita Venkatesan, Natasha Pandit, Heidi M. Schambra, Carlos Fernandez-Granda
Towards data-driven stroke rehabilitation via wearable sensors and deep learning. MLHC (2020)
Joseph McDonald, Brett Bernstein, Carlos Fernandez-Granda
A Sampling Theorem for Deconvolution in Two Dimensions. SIAM J. Imaging Sci. 13 (4) (2020)
Dev Yashpal Sheth, Sreyas Mohan, Joshua L. Vincent, Ramon Manzorro, Peter A. Crozier, Mitesh M. Khapra, Eero P. Simoncelli, Carlos Fernandez-Granda
Unsupervised Deep Video Denoising. CoRR (2020)
Joseph McDonald, Brett Bernstein, Carlos Fernandez-Granda
A Sampling Theorem for Deconvolution in Two Dimensions. CoRR (2020)
Pau Batlle, Joan Bruna, Carlos Fernandez-Granda, Victor M. Preciado
Adaptive Test Allocation for Outbreak Detection and Tracking in Social Contact Networks. CoRR (2020)
Sreyas Mohan, Zahra Kadkhodaie, Eero P. Simoncelli, Carlos Fernandez-Granda
Robust And Interpretable Blind Image Denoising Via Bias-Free Convolutional Neural Networks. ICLR (2020)
Sheng Liu, Jonathan Niles-Weed, Narges Razavian, Carlos Fernandez-Granda
Early-Learning Regularization Prevents Memorization of Noisy Labels. CoRR (2020)
Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanislaw Jastrzebski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. CoRR (2020)
Gautier Izacard, Sreyas Mohan, Carlos Fernandez-Granda
Data-driven Estimation of Sinusoid Frequencies. NeurIPS (2019)
Gautier Izacard, Sreyas Mohan, Carlos Fernandez-Granda
Data-driven Estimation of Sinusoid Frequencies. CoRR (2019)
Sreyas Mohan, Zahra Kadkhodaie, Eero P. Simoncelli, Carlos Fernandez-Granda
Robust and interpretable blind image denoising via bias-free convolutional neural networks. CoRR (2019)
Sheng Liu, Chhavi Yadav, Carlos Fernandez-Granda, Narges Razavian
On the design of convolutional neural networks for automatic detection of Alzheimer's disease. ML4H@NeurIPS (2019)
Brett Bernstein, Sheng Liu, Chrysa Papadaniil, Carlos Fernandez-Granda
Sparse Recovery Beyond Compressed Sensing: Separable Nonlinear Inverse Problems. CoRR (2019)
Gautier Izacard, Brett Bernstein, Carlos Fernandez-Granda
A Learning-based Framework for Line-spectra Super-resolution. ICASSP (2019)
Sheng Liu, Chhavi Yadav, Carlos Fernandez-Granda, Narges Razavian
On the design of convolutional neural networks for automatic detection of Alzheimer's disease. CoRR (2019)
Sheng Liu, Mark Cheng, Hayley Brooks, Wayne E. Mackey, David J. Heeger, Esteban G. Tabak, Carlos Fernandez-Granda
Time-Series Analysis via Low-Rank Matrix Factorization Applied to Infant-Sleep Data. CoRR (2019)
Sunli Tang, Carlos Fernandez-Granda, Sylvain Lannuzel, Brett Bernstein, Riccardo Lattanzi, Martijn A. Cloos, Florian Knoll, Jakob Assländer
Multicompartment Magnetic Resonance Fingerprinting. CoRR (2018)
Gautier Izacard, Brett Bernstein, Carlos Fernandez-Granda
A Learning-Based Framework for Line-Spectra Super-resolution. CoRR (2018)
Brett Bernstein, Carlos Fernandez-Granda
Deconvolution of Point Sources: A Sampling Theorem and Robustness Guarantees. CoRR (2017)
Carlos Fernandez-Granda, Gongguo Tang, Xiaodong Wang, Le Zheng
Demixing Sines and Spikes: Robust Spectral Super-resolution in the Presence of Outliers. CoRR (2016)
Carlos Fernandez-Granda
Super-Resolution of Point Sources via Convex Programming. CoRR (2015)
Carlos Fernandez-Granda
Super-resolution of point sources via convex programming. CAMSAP (2015)
Carlos Fernandez-Granda, Emmanuel J. Candès
Super-resolution via Transform-Invariant Group-Sparse Regularization. ICCV (2013)
Carlos Fernandez-Granda
Support detection in super-resolution CoRR (2013)
Emmanuel J. Candès, Carlos Fernandez-Granda
Towards a Mathematical Theory of Super-Resolution CoRR (2012)
Emmanuel J. Candès, Carlos Fernandez-Granda
Super-Resolution from Noisy Data CoRR (2012)