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Doing small network scientific machine learning in Julia 5x faster than PyTorch

Julia · published 14 April 2022

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https://fluxml.ai/

fluxml.ai

https://github.com/PumasAI/SimpleChains.jl

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https://pumas.ai/

pumas.ai

https://juliahub.com/

juliahub.com

https://www.roche.com/

roche.com

https://www.pharmacy.umaryland.edu/centers/ctm/

pharmacy.umaryland.edu

The Essential Tools of Scientific Machine Learning (Scientific ML) Read at the source ↗

stochasticlifestyle.com

https://sciml.ai/roadmap/

sciml.ai

https://arxiv.org/abs/2001.04385

arxiv.org

https://youtu.be/6hhF6Llv4sI?t=342

youtu.be

Engineering Trade-Offs in Automatic Differentiation: from TensorFlow and PyTorch to Jax and Julia Read at the source ↗

stochasticlifestyle.com

https://github.com/SciML/DiffEqFlux.jl/blob/v1.8.1/src/fast_layers.jl

github.com

https://github.com/JuliaSIMD/LoopVectorization.jl/

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https://github.com/chriselrod/MatrixExponentialTorch

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https://gist.github.com/patrick-kidger/68bf7b99ba02c246b20eaa38f2ad3d38

gist.github.com

https://github.com/chriselrod/LeNetTorch

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https://github.com/FluxML/Flux.jl

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https://github.com/PumasAI/SimpleChains.jl/blob/main/examples/mnist_lenet.jl

github.com