AdasOptimizer VS ML-Optimizers-JAX

Compare AdasOptimizer vs ML-Optimizers-JAX and see what are their differences.

AdasOptimizer

ADAS is short for Adaptive Step Size, it's an optimizer that unlike other optimizers that just normalize the derivative, it fine-tunes the step size, truly making step size scheduling obsolete, achieving state-of-the-art training performance (by YanaiEliyahu)
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AdasOptimizer ML-Optimizers-JAX
2 1
85 40
- -
5.8 4.5
over 3 years ago almost 3 years ago
C++ Python
MIT License -
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.
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AdasOptimizer

Posts with mentions or reviews of AdasOptimizer. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-01-15.

ML-Optimizers-JAX

Posts with mentions or reviews of ML-Optimizers-JAX. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing AdasOptimizer and ML-Optimizers-JAX you can also consider the following projects:

DemonRangerOptimizer - Quasi Hyperbolic Rectified DEMON Adam/Amsgrad with AdaMod, Gradient Centralization, Lookahead, iterative averaging and decorrelated Weight Decay

RAdam - On the Variance of the Adaptive Learning Rate and Beyond

imagenette - A smaller subset of 10 easily classified classes from Imagenet, and a little more French

pytorch-optimizer - torch-optimizer -- collection of optimizers for Pytorch

dm-haiku - JAX-based neural network library

tensorflow - An Open Source Machine Learning Framework for Everyone

trax - Trax — Deep Learning with Clear Code and Speed

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).