A new method developed at LMU overcomes fundamental resolution limits and may provide insights into high-temperature ...

The painstaking process of formalization to verify proofs is starting to surge thanks to AI. That could radically change the ...

Abstract: Graph Convolutional neural Networks (GCNs) demonstrate exceptional effectiveness when working with data that have non-Euclidean structures. In recent years, numerous researchers have ...

Abstract: Convolutional neural network (CNN) accelerators implemented on Field-Programmable Gate Arrays (FPGAs) are typically designed with a primary focus on maximizing performance, often measured in ...

In seismic exploration, raw data recorded at the surface does not provide a true map of the subsurface. The primary challenge, addressed in this project, is Spatial Aliasing and Diffraction Overlap.