torchcvnn: A PyTorch-based library to easily experiment with state-of-the-art Complex-Valued Neural Networks
Résumé
Complex-valued neural networks (CVNN) have attracted increasing attention in recent years, although their definition dates back to the mid-20th century. Indeed, several domains naturally process complex-valued signals, such as when sensing involves the response to an electromagnetic wave, such as remote sensing, MRI, etc. These domains would benefit from breakthroughs in complex-valued neural networks (CVNNs). We believe independent contributions to CVNNs must be gathered in a single, easy-to-use library. \texttt{torchcvnn} is an effort in that direction and provides several complex-valued building blocks, allowing us to experiment with CVNNs easily. The library is available at \url{https://github.com/torchcvnn/torchcvnn} alongside examples available at \url{https://github.com/torchcvnn/examples}.
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