Abstract: Graph Convolution Networks (GCNs) have achieved remarkable success in representation of structured graph data. As we know that traditional GCNs are generally defined on the fixed first-order ...

Abstract: In this paper, we present a novel convolution theorem which encompasses the well known convolution theorem in (graph) signal processing as well as the one related to time-varying filters.

Our research proves a conjecture from string theory asserting the vanishing of a specific convolution sum arising in the 4-graviton scattering amplitude in 10-dimensional type IIB string theory. The ...

MATLAB-based Digital Signal Processing Laboratory with examples of convolution, DFT, FIR filtering, and more. Each folder includes code and individual README files for theoretical explanations.

MATLAB-based Digital Signal Processing Laboratory with examples of convolution, DFT, FIR filtering, and more. Each folder includes code and individual README files for theoretical explanations.

Cavendish Laboratory, Department of Physics, University of Cambridge, J. J. Thomson Avenue, Cambridge CB3 0HE, U.K. ISIS Neutron and Muon Source, STFC Rutherford Appleton Laboratory, Harwell Science ...

Light-weight convolutional neural networks (CNNs) suffer performance degradation as their low computational budgets constrain both the depth (number of convolution layers) and width (number of ...