14 citations · 58 across the 16 of their papers we have counts for
3 papers · 2 filters
ManifoldNet: A Deep Network Framework for Manifold-valued Data
Rudrasis Chakraborty, Jose Bouza, Jonathan Manton +1
Deep neural networks have become the main work horse for many tasks involving learning from data in a variety of applications in Science and Engineering. Traditionally, the input t…
Dictionary Learning and Sparse Coding on Statistical Manifolds
Rudrasis Chakraborty, Monami Banerjee, Baba C. Vemuri
In this paper, we propose a novel information theoretic framework for dictionary learning (DL) and sparse coding (SC) on a statistical manifold (the manifold of probability distrib…
A CNN for homogneous Riemannian manifolds with applications to Neuroimaging
Rudrasis Chakraborty, Monami Banerjee, Baba C. Vemuri
Convolutional neural networks are ubiquitous in Machine Learning applications for solving a variety of problems. They however can not be used in their native form when the domain o…