5 papers
Neural collapse in the orthoplex regime
James Alcala, Rayna Andreeva, Vladimir A. Kobzar +4
When training a neural network for classification, the feature vectors of the training set are known to collapse to the vertices of a regular simplex, provided the dimension of…
Learning collective variables that respect permutational symmetry
Jiaxin Yuan, Shashank Sule, Yeuk Yin Lam +1
In addition to translational and rotational symmetries, clusters of identical interacting particles possess permutational symmetry. Coarse-grained models for such systems are instr…
Learning collective variables that preserve transition rates
Shashank Sule, Arnav Mehta, Maria K. Cameron
Collective variables (CVs) play a crucial role in capturing rare events in high-dimensional systems, motivating the continual search for principled approaches to their design. In t…
Neumann eigenmaps for landmark embedding
Shashank Sule, Wojciech Czaja
We present Neumann eigenmaps (NeuMaps), a novel approach for enhancing the standard diffusion map embedding using landmarks, i.e distinguished samples within the dataset. By interp…
Input layer regularization and automated regularization hyperparameter tuning for myelin water estimation using deep learning
Mirage Modi, Shashank Sule, Jonathan Palumbo +4
We propose a novel deep learning method which combines classical regularization with data augmentation for estimating myelin water fraction (MWF) in the brain via biexponential ana…