Getting started with EvoNet

EvoNet aims to provide a machine learning framework that can optimize both network weights AND network structure simultaneously while still taking advantage of the latest hardware acceleration technology (Fig 1).

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Currently, network structure is optimized using an evolutionary algorithm over network node integration and activation functions and over node connections (Fig 2), while network weights are optimized using standard backpropogation.

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EvoNet is written in C++ and is optimized for hardware acceleration using native threading and CUDA GPU technology.

Quick Start

Download SmartPeak from GitHub.