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comp-physics · Aug 1, 2023 · 378a937 · 378a937
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-roseNNA is a fast, portable, and minimally-intrusive library for neural network inference.
+RoseNNa is a fast, portable, and minimally-intrusive library for neural network inference.
 It can run inference on neural networks in [ONNX](https://onnx.ai/) format, which is universal and can be used with PyTorch, TensorFlow, Keras, and more.
-roseNNa's intended use case is large Fortran- and C-based HPC codebases. 
+RoseNNa's intended use case is large Fortran- and C-based HPC codebases. 
 It currently supports RNNs, CNNs, and MLPs, though more architectures are in the works.
 The library is optimized Fortran and outperforms PyTorch (by a factor between 2 and 5x) for the relatively small neural networks used in physics applications, like CFD.
+It is described in detail in the following manuscript: <a href="http://arxiv.org/abs/2307.16322">A. Bati, S. H. Bryngelson (2023) arXiv 2307.16322</a>.
 
 ## Hello RoseNNa