tf-madgrad
A tf.keras implementation of Facebook AI's MadGrad optimization algorithm (by DarshanDeshpande)
evotorch
Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE. (by nnaisense)
tf-madgrad | evotorch | |
---|---|---|
1 | 14 | |
20 | 972 | |
- | 0.9% | |
0.0 | 4.7 | |
almost 2 years ago | 2 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tf-madgrad
Posts with mentions or reviews of tf-madgrad.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Implementation of MADGRAD optimization algorithm for Tensorflow
You can check out the repository here for more examples and test cases. If you like the work then considering giving it a star! :)
evotorch
Posts with mentions or reviews of evotorch.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-26.
- [P] EvoTorch 0.4.0 dropped with GPU-accelerated implementations of CMA-ES, MAP-Elites and NSGA-II.
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Question on how to model a "discontinuous" action space
population based algos dont care about differentiability https://github.com/google/evojax https://github.com/RobertTLange/evosax https://github.com/nnaisense/evotorch https://github.com/uber-research/PyTorch-NEAT
- Should I pursue Evolutionary Strategies?
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[P] We’ve released EvoTorch 0.3.0, with VecGymNE, memory usage improvements, Colab support and more! VecGymNE enables evolutionary RL with vectorized environments and policies, especially massively parallel simulators like Brax!
Check out the release and try it now: https://github.com/nnaisense/evotorch/releases/tag/v0.3.0
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[P] Participating in the Myosuite challenge at NeurIPS2022 on dexterous control? We are releasing a baseline and starter code to help you get started using EvoTorch!
EvoTorch (evotorch.ai) makes it straightforward to apply evolutionary reinforcement learning to the challenge. We've included setup help, training and visualisation scripts, a baseline controller trained through the provided script and help for submission to the competition. Simply head to the public GitHub to get started: https://github.com/nnaisense/evotorch-myosuite-starter
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NNAISENSE Open-Sources ‘EvoTorch’: An Evolutionary Algorithm Library for the Machine Learning Community
An Advanced Evolutionary library or algorithm has been a dream of scientists and AI/ML enthusiasts since the concept was introduced. This vision has come true thanks to the scientists at NNAISENSE, a Switzerland-based AI Enterprise. They created an open-source platform called EvoTorch. When operated in combination with Machine Learning, it can solve complex operational problems in a fraction of time, with lower costs, and at a larger scale. Evolutionary algorithms act as a step toward solving cascading problems that occur when the problem’s size and complexity increase. Evolutionary algorithms make the situations easier to handle the complexity without adding to the cost, they are also much easier to connect through GPUs and CPUs parallelly to ease up the calculation time and the complexity associated with it, that the only limit to your computational power becomes your budget. The evolutionary algorithms are built in the open framework EvoTorch.
- Next-Generation Evolutionary Search, Learning and Planning
- NNAISENSE releases EvoTorch (evotorch.ai): An open-source Evolutionary Algorithm Library with multi-CPU/multi-GPU support for massive evolutionary experiments!
- NNAISENSE releases EvoTorch: An open-source Evolutionary Algorithm Library with multi-CPU/multi-GPU support for massive evolutionary experiments!
What are some alternatives?
When comparing tf-madgrad and evotorch you can also consider the following projects:
evojax
deep-neuroevolution - Deep Neuroevolution
de-torch - Minimal PyTorch Library for Differential Evolution
talk-generator - talk-generator is capable of generating coherent slide decks based on a single topic suggestion.
PyTorch-NEAT
pytorch-forecasting - Time series forecasting with PyTorch
pyshgp - Push Genetic Programming in Python.
evotorch-myosuite-starter
tiny_gp - Tiny Genetic Programming in Python
evolution-strategies-starter - Code for the paper "Evolution Strategies as a Scalable Alternative to Reinforcement Learning"
SpaceDrones - A simple learning environment with space drones for evolution-inspired optimization.
evosax - Evolution Strategies in JAX 🦎
evotorch vs evojax
evotorch vs deep-neuroevolution
evotorch vs de-torch
evotorch vs talk-generator
evotorch vs PyTorch-NEAT
evotorch vs pytorch-forecasting
evotorch vs pyshgp
evotorch vs evotorch-myosuite-starter
evotorch vs tiny_gp
evotorch vs evolution-strategies-starter
evotorch vs SpaceDrones
evotorch vs evosax