Interactive Generative Manifold Learning

Signal Innovations Group (SIG) proposes a Phase II program that addresses three primary capabilities for applications involving high-dimensional observed data: reversible nonlinear data dimensionality reduction, static and dynamic synthesis of data in the observed space based on a low-dimensional latent space, and intuitive and meaningful human interaction with the data in both the observed and latent spaces. Each of these three capabilities will be addressed in the Phase II Base effort through the development of models and algorithms, visualization techniques, and a prototype user interface. Additionally, proposed Phase II Options 1 and 2 will focus on maturing and optimizing the technology and software, ultimately leading to transition and integration with a targeted program of record.