Convolution neural networks (CNNs) have been extensively used in machine learning applications. The most time-consuming part of CNNs are convolution operations. A common approach to implementing ...

CUTLASS Convolution Implicit GEMM is the formulation of a convolution operation as a GEMM (generalized matrix-matrix product). Convolution takes an activation tensor and applies a sliding filter on it ...

Convolutional neural networks (CNNs) have emerged as one of the most successful machine learning technologies for image and video processing. The most computationally-intensive parts of CNNs are the ...

CUTLASS Convolution Implicit GEMM is the formulation of a convolution operation as a GEMM (generalized matrix-matrix product). Convolution takes an activation tensor and applies a sliding filter on it ...

, L. Longhi, M. Perlstadt, Differential Operators Commuting with Finite Convolution Integral Operators: Some Non-Abelian Examples, SIAM Journal on Applied Mathematics ...

The target detector for the radar system further includes sequentially processing the reflection signals, rejecting cross talk from the clutter correlation matrix, and increasing a ...