Assimilation of spatially- and temporally-distributed state observations into simulations of dynamical systems stemming from discretized PDEs leads to inverse problems with high-di...
Omar Bashir, Omar Ghattas, Judith Hill, Bart G. va...
Abstract. We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date...
The detection of genes that show similar profiles under different experimental conditions is often an initial step in inferring the biological significance of such genes. Visualiz...
In this paper we introduce a novel approach to manifold alignment, based on Procrustes analysis. Our approach differs from "semisupervised alignment" in that it results ...
We present a new visualization of the distance and cluster structure of high dimensional data. It is particularly well suited for analysis tasks of users unfamiliar with complex d...