eLife

Designing optimal perturbation inputs for system identification in neuroscience

To enable more accurate estimation of connectivity, we propose a data-driven and theoretically grounded framework for optimally designing perturbation inputs, based on formulating the neural model as ...
IEEE

A Gaussian Process-Regularized Graphical Learning Method for Distribution System State Estimation Using Extremely Scarce State Variable Labels

Abstract: Learning-based distribution system state estimation (DSSE) methods typically depend on sufficient fully labeled data to construct mapping functions. However, collecting historical labels ...
The Debrief

Scientists Successfully Use String Theory to Challenge More Than a Century of Assumptions About Living Systems

Scientists from Rensselaer Polytechnic Institute (RPI) have used mathematical concepts from string theory, a theoretical description of the mechanics of the entire universe, to upend over a century of ...
IEEE

Traffic Scene Representation and Encoding With Graph Structure Learning and Exploration

Abstract: Effective scene representation is critical for trajectory generation tasks in autonomous driving. Existing attention-based methods often rely on fixed-length input elements, limiting their ...