simple-es
TorchGA
| simple-es | TorchGA | |
|---|---|---|
| 1 | 3 | |
| 14 | 86 | |
| - | - | |
| 0.0 | 4.3 | |
| over 2 years ago | 11 months ago | |
| Python | Python | |
| Apache License 2.0 | - |
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simple-es
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Multi-agent Evolutionary strategies using PyTorch
There have been many studies that combine RL and ES(evolutionary strategies), and combining these methods and multi-agent reinforcement learning is my current interest. As a one who has only studied RL and has no knowledge of ES, I have created a multi-agent evolutionary strategies project using pytorch, simple-es.
TorchGA
- PyGAD 2.13.0 Released! A Python 3 Library for Building the Genetic Algorithm and Training Machine Learning Algorithms (Supports Keras and PyTorch)
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Train PyTorch Models Using Genetic Algorithm with PyGAD
Link of the GitHub project that prepares the PyTorch models for use with PyGAD: https://github.com/ahmedfgad/TorchGA
The source code of the pygad.torchga module is available at the ahmedfgad/TorchGA GitHub project.
What are some alternatives?
nes-torch - Minimal PyTorch Library for Natural Evolution Strategies
koila - Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code.
de-torch - Minimal PyTorch Library for Differential Evolution
PySR - High-Performance Symbolic Regression in Python and Julia
snntorch - Deep and online learning with spiking neural networks in Python
bittensor - Internet-scale Neural Networks
awesome-colab-notebooks - Collection of google colaboratory notebooks for fast and easy experiments
image-background-remove-tool - ✂️ Automated high-quality background removal framework for an image using neural networks. ✂️
pycox - Survival analysis with PyTorch
torchsynth - A GPU-optional modular synthesizer in pytorch, 16200x faster than realtime, for audio ML researchers.
tinysleepnet - TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College London respectively
torchinfo - View model summaries in PyTorch!