We propose the geometry-informed neural operator (GINO), a highly effici...
Topology Optimization is the process of finding the optimal arrangement ...
Physics-Informed Neural Networks (PINNs) are a class of deep neural netw...
We present SimNet, an AI-driven multi-physics simulation framework, to
a...
In this paper, we propose the Adaptive Physics-Informed Neural Networks
...
This paper presents a novel physics-informed regularization method for
t...
Developing efficient numerical algorithms for high dimensional random Pa...
Natural disasters can have catastrophic impacts on the functionality of
...