20 citations · 51 across the 13 of their papers we have counts for
13 papers
Optimal Transport for Kernel Gaussian Mixture Models
Jung Hun Oh, Rena Elkin, Anish Kumar Simhal +3
The Wasserstein distance from optimal mass transport (OMT) is a powerful mathematical tool with numerous applications that provides a natural measure of the distance between two pr…
Promotion/Inhibition Effects in Networks: A Model with Negative Probabilities
Anqi Dong, Tryphon T. Georgiou, Allen Tannenbaum
Biological networks often encapsulate promotion/inhibition as signed edge-weights of a graph. Nodes may correspond to genes assigned expression levels (mass) of respective proteins…
Wasserstein Image Local Analysis: Histogram of Orientations, Smoothing and Edge Detection
Jiening Zhu, Harini Veeraraghavan, Larry Norton +2
The Histogram of Oriented Gradient is a widely used image feature, which describes local image directionality based on numerical differentiation. Due to its ill-posed nature, small…
Visualizing fluid flows via regularized optimal mass transport with applications to neuroscience
Xinan Chen, Anh Phong Tran, Rena Elkin +2
Regularized optimal mass transport (rOMT) problem adds a diffusion term to the continuity equation in the original dynamic formulation of the optimal mass transport (OMT) problem p…
A Vectorial Approach to Unbalanced Optimal Mass Transport
Jiening Zhu, Rena Elkin, Jung Hun Oh +2
Unbalanced optimal mass transport (OMT) seeks to remove the conservation of mass constraint by adding a source term to the standard continuity equation in the Benamou-Brenier formu…
Controlled and Uncontrolled Stochastic Norton-Simon-Massagué Tumor Growth Models
Zehor Belkhatir, Michele Pavon, James C. Mathews +4
Tumorigenesis is a complex process that is heterogeneous and affected by numerous sources of variability. This study presents a stochastic extension of a biologically grounded tumo…