NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training

Last update: Dec 05, 2022

Overview

NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training

It is NEAT but the weights are trained with Natural Evolution Strategy and the weights are shared across genomes.

Requirements

numpy
cloudpickle

Install

pip install nesneat

Optional

matplotlib # To draw networks
mpi4py # For parallelization
gym # For examples

Usage

Check examples

PYTHONPATH="$(pwd):$PYTHONPATH" python examples/cartpole.py
# Or in parallel
PYTHONPATH="$(pwd):$PYTHONPATH" mpirun -np 2 python examples/cartpole.py

Owner

Göktuğ Karakaşlı

Computer Science MSc. and Electronics engineer working on Machine Learning, Robotics, Computer Vision.

GitHub Repository

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NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training

Related tags

Overview

NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training

Requirements

Install

Optional

Usage

Owner

Göktuğ Karakaşlı

A simple Neural Network that predicts the label for a series of handwritten digits

PyTorch implementation of our Adam-NSCL algorithm from our CVPR2021 (oral) paper "Training Networks in Null Space for Continual Learning"

An inofficial PyTorch implementation of PREDATOR based on KPConv.

For AILAB: Cross Lingual Retrieval on Yelp Search Engine

Multiview 3D object detection on MultiviewC dataset through moft3d.

This is code to fit per-pixel environment map with spherical Gaussian lobes, using LBFGS optimization

Code of 3D Shape Variational Autoencoder Latent Disentanglement via Mini-Batch Feature Swapping for Bodies and Faces

Code for sound field predictions in domains with impedance boundaries. Used for generating results from the paper

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MicroNet: Improving Image Recognition with Extremely Low FLOPs (ICCV 2021)

I tried to apply the CAM algorithm to YOLOv4 and it worked.

TransNet V2: Shot Boundary Detection Neural Network

Distributional Sliced-Wasserstein distance code

This application is the basic of automated online-class-joiner(for YıldızEdu) within the right time. Gets the ZOOM link by scheduled date and time.

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CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP

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