Alex Fedorov

According to our database, Alex Fedorov authored at least 16 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links.

Alex Fedorov, Eloy Geenjaar, Lei Wu, Tristan Sylvain, Thomas P. DeRamus, Margaux Luck, Maria B. Misiura, Girish Mittapalle, R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun

NeuroImage, January, 2024

2022

Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes.

Alex Fedorov, Eloy Geenjaar, Lei Wu, Tristan Sylvain, Thomas P. DeRamus, Margaux Luck, Maria B. Misiura, R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun

CoRR, 2022

Pipeline-Invariant Representation Learning for Neuroimaging.

Xinhui Li, Alex Fedorov, Mrinal Mathur, Anees Abrol, Gregory Kiar, Sergey M. Plis, Vince D. Calhoun

CoRR, 2022

2021

Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data.

Alex Fedorov, Eloy Geenjaar, Lei Wu, Thomas P. DeRamus, Vince D. Calhoun, Sergey M. Plis

CoRR, 2021

On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer's Disease.

Alex Fedorov, Lei Wu, Tristan Sylvain, Margaux Luck, Thomas P. DeRamus, Dmitry Bleklov, Sergey M. Plis, Vince D. Calhoun

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease.

Alex Fedorov, Tristan Sylvain, Eloy Geenjaar, Margaux Luck, Lei Wu, Thomas P. DeRamus, Alex Kirilin, Dmitry Bleklov, Vince D. Calhoun, Sergey M. Plis

Proceedings of the 9th IEEE International Conference on Healthcare Informatics, 2021

2020

Taxonomy of multimodal self-supervised representation learning.

Alex Fedorov, Tristan Sylvain, Margaux Luck, Lei Wu, Thomas P. DeRamus, Alex Kirilin, Dmitry Bleklov, Vince D. Calhoun, Sergey M. Plis

CoRR, 2020

On self-supervised multi-modal representation learning: An application to Alzheimer's disease.

Alex Fedorov, Lei Wu, Tristan Sylvain, Margaux Luck, Thomas P. DeRamus, Dmitry Bleklov, Sergey M. Plis, Vince D. Calhoun

CoRR, 2020

Whole MILC: Generalizing Learned Dynamics Across Tasks, Datasets, and Populations.

Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Noah Lewis, Zening Fu, Vince D. Calhoun, Sergey M. Plis

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2019

Learnt dynamics generalizes across tasks, datasets, and populations.

Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Zening Fu, Vince D. Calhoun, Sergey M. Plis

CoRR, 2019

Transfer Learning of fMRI Dynamics.

Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Zening Fu, Sergey M. Plis

CoRR, 2019

Learning deep representations by mutual information estimation and maximization.

R. Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler, Yoshua Bengio

Proceedings of the 7th International Conference on Learning Representations, 2019

Prediction of Progression to Alzheimer's disease with Deep InfoMax.

Alex Fedorov, R. Devon Hjelm, Anees Abrol, Zening Fu, Yuhui Du, Sergey M. Plis, Vince D. Calhoun

Proceedings of the 2019 IEEE EMBS International Conference on Biomedical & Health Informatics, 2019

2018

Learning deep representations by mutual information estimation and maximization.

R. Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Adam Trischler, Yoshua Bengio

CoRR, 2018

2017

Almost instant brain atlas segmentation for large-scale studies.

Alex Fedorov, Eswar Damaraju, Vince D. Calhoun, Sergey M. Plis

CoRR, 2017

End-to-end learning of brain tissue segmentation from imperfect labeling.

Alex Fedorov, Jeremy Johnson, Eswar Damaraju, Alexei Ozerin, Vince D. Calhoun, Sergey M. Plis

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017