The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...
Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ...
Koch, J. (2025) Entangled Cyclical Encryption Architecture: The Paradigm Cipher for a Fractured World . Journal of ...
Abstract: The paper presents a new technique for parametric optimization of diode-connected transistor mixers. Parametric optimization is based on the criterion of conversion gain maximization and on ...
Physics-based machine learning unlocks 3D printing potential, thanks to work from Lehigh University's Parisa Khodabakhshi.
University of Queensland researchers have created a microscopic "ocean" on a silicon chip to miniaturize the study of wave ...
A new method developed at the University of Warwick offers the first simple and predictive way to calculate how irregularly ...
Toni Townes-Whitley didn’t follow a step-by-step blueprint to reach the top of the defense industry. The SAIC CEO’s path was ...
Abstract: Online gait planning plays a crucial role for the locomotion of humanoid robots. While simplified models often fail to capture critical dynamic features of the robot’s motion, making online ...
Evaluating the advantages and potential drawbacks of shielding as a method for safe RL. Bettina Könighofer is an assistant ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback