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- evogp Public
A GPU-accelerated library for Tree-based Genetic Programming, leveraging PyTorch and custom CUDA kernels for high-performance evolutionary computation. It supports symbolic regression, classification, and policy optimization with advanced features like multi-output trees and benchmark tools.
EMI-Group/evogp’s past year of commit activity - evorl Public
EvoRL is a fully GPU-accelerated framework for Evolutionary Reinforcement Learning, implemented with JAX. It supports Reinforcement Learning (RL), Evolutionary Computation (EC), Evolution-guided Reinforcement Learning (ERL), AutoRL, and seamless integration with GPU-optimized simulation environments.
EMI-Group/evorl’s past year of commit activity - evoxbench Public
Transforming Neural Architecture Search (NAS) into multi-objective optimization problems. A benchmark suite for testing evolutionary algorithms in deep learning.
EMI-Group/evoxbench’s past year of commit activity - metade Public
MetaDE is a GPU-accelerated evolutionary framework that optimizes Differential Evolution (DE) strategies via meta-level evolution. Supporting both JAX and PyTorch, it dynamically adapts mutation and crossover strategies for efficient large-scale black-box optimization.
EMI-Group/metade’s past year of commit activity - istratde Public
iStratDE is a GPU-accelerated Differential Evolution framework that enhances performance through individual-level strategy diversity. By assigning unique, fixed strategies to each individual at initialization, it achieves robust, communication-free optimization without complex adaptation mechanisms. Supporting both JAX and PyTorch backends.
EMI-Group/istratde’s past year of commit activity
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