With the overwhelming amount of data available both on and offline today...
Literature on machine learning for multiple sclerosis has primarily focu...
Machine learning (ML) approaches have demonstrated promising results in ...
Fairness and robustness are often considered as orthogonal dimensions wh...
A collection of the accepted abstracts for the Machine Learning for Heal...
A collection of the accepted abstracts for the Machine Learning for Heal...
Machine-learning automation tools, ranging from humble grid-search to
hy...
Electroencephalograms (EEG) are often contaminated by artifacts which ma...
Systems that can automatically analyze EEG signals can aid neurologists ...
Automatic epileptic seizure analysis is important because the differenti...
Accurate classification of seizure types plays a crucial role in the
tre...
Deep learning object detectors achieve state-of-the-art accuracy at the
...
Brain-related disorders such as epilepsy can be diagnosed by analyzing
e...
In this article, a novel neuro-inspired low-resolution online unsupervis...
In this article, we propose a novel Winner-Take-All (WTA) architecture
e...
In this paper, a neuron with nonlinear dendrites (NNLD) and binary synap...