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Nemo is an individual-based, forward-time, genetically explicit, and stochastic simulation software designed for the study of the evolution of life history and quantitative traits, and genetic markers under various types of selection, in a spatially explicit, metapopulation framework.
Mocha.jl is a deep learning framework for Julia, inspired by the C++ Caffe framework. It offers efficient implementations of gradient descent solvers and common neural network layers, supports optional unsupervised pre-training, and allows switching to a GPU backend for accelerated performance. The development of Mocha.jl happens in relative early days of Julia. Now that both Julia and the ecosystem has evolved significantly, and with some exciting new tech such as writing GPU kernels...