Training standard AI models against a diverse pool of opponents — rather than building complex hardcoded coordination rules — ...

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 ...

In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...

However, in indoor environments, non-line-of-sight (NLOS) signals significantly degrade the ranging performance of UWB ...