Achieving high reliability in AI systems—such as autonomous vehicles that stay on course even in snowstorms or medical AI ...

A new technical paper titled “An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design” was published by researchers at the University of Texas at Austin, Nvidia ...

Abstract Model robustness indicates a model's capability to generalize well on unforeseen distributional shifts, including data corruptions and ...

Georgia Tech researchers Vidya Muthukumar and Eva Dyer are leading a multi-institutional project to develop a theory for data augmentation, aiming to improve the generalization and fairness of AI ...

AI agents—capable of autonomous decision making and action—are emerging as transformative enterprise tools. While discussions about agentic AI often center on sophisticated algorithms and model ...