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Monami Banerjee

4 accepted papers

2018

A Statistical Recurrent Model on the Manifold of Symmetric Positive Definite Matrices

NeurIPS 2018poster

In a number of disciplines, the data (e.g., graphs, manifolds) to be analyzed are non-Euclidean in nature. Geometric deep learning corresponds to techniques that generalize deep neural network models to such non-Euclidean spaces. Several recent papers have shown how convolutional neural networks (C…

2016

A Nonlinear Regression Technique for Manifold Valued Data With Applications to Medical Image Analysis

CVPR 2016poster

Regression is an essential tool in Statistical analysis of data with many applications in Computer Vision, Machine Learning, Medical Imaging and various disciplines of Science and Engineering. Linear and nonlinear regression in a vector space setting has been well studied in literature. However, gen…

Cited by 52PDFScholar
2015

Interpolation on the Manifold of K Component GMMs

ICCV 2015poster

Probability density functions (PDFs) are fundamental "objects" in mathematics with numerous applications in computer vision, machine learning and medical imaging. The feasibility of basic operations such as computing the distance between two PDFs and estimating a mean of a set of PDFs is a direct fu…

Cited by 6PDFScholar