2 papers
cs.LG2026
Enhancing Physics-Informed Neural Networks with Domain-aware Fourier Features: Towards Improved Performance and Interpretable Results
Alberto Miño Calero, Luis Salamanca, Konstantinos E. Tatsis
Physics-Informed Neural Networks (PINNs) incorporate physics into neural networks by embedding partial differential equations (PDEs) into their loss function. Despite their success…
cs.RO2026
Learning to Build: Autonomous Robotic Assembly of Stable Structures Without Predefined Plans
Jingwen Wang, Johannes Kirschner, Paul Rolland +2
This paper presents a novel autonomous robotic assembly framework for constructing stable structures without relying on predefined architectural blueprints. Instead of following fi…