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09/07/2022
Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes
Recent neuroimaging studies that focus on predicting brain disorders via...
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03/29/2021
Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data
Self-supervised learning has enabled significant improvements on natural...
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12/25/2020
Taxonomy of multimodal self-supervised representation learning
Sensory input from multiple sources is crucial for robust and coherent h...
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12/25/2020
On self-supervised multi-modal representation learning: An application to Alzheimer's disease
Introspection of deep supervised predictive models trained on functional...
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07/29/2020
Whole MILC: generalizing learned dynamics across tasks, datasets, and populations
Behavioral changes are the earliest signs of a mental disorder, but argu...
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11/16/2019
Transfer Learning of fMRI Dynamics
As a mental disorder progresses, it may affect brain structure, but brai...
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04/24/2019
Prediction of Progression to Alzheimer`s disease with Deep InfoMax
Arguably, unsupervised learning plays a crucial role in the majority of ...
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08/20/2018
Learning deep representations by mutual information estimation and maximization
Many popular representation-learning algorithms use training objectives ...
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11/01/2017
Almost instant brain atlas segmentation for large-scale studies
Large scale studies of group differences in healthy controls and patient...
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12/03/2016
