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PyTorch implementation of "Efficient Neural Architecture Search
ENAS in PyTorch is a PyTorch implementation of Efficient Neural Architecture Search (ENAS), a method that automates the design of neural network architectures through reinforcement learning and parameter sharing. The repository demonstrates how a controller network can explore a large search space and discover high-performing architectures while dramatically reducing the computational cost traditionally associated with neural architecture search.
Development and support of OCFA have been discontinued. the code has moved to these github repositories:
https://github.com/DNPA/OcfaLib
https://github.com/DNPA/OcfaArch
https://github.com/DNPA/OcfaJavaLib
https://github.com/DNPA/OcfaModules
https://github.com/DNPA/OcfaDoc
If you are interested in contributing to ongoing work on the creation of a community maintained OCFA inspired computer forensic framework, please join the Mattock/MattockFS community page on...