optimas
Optimization at scale, powered by libEnsemble (by optimas-org)
Ax
Adaptive Experimentation Platform (by facebook)
| optimas | Ax | |
|---|---|---|
| 1 | 3 | |
| 20 | 2,275 | |
| - | 1.2% | |
| 9.7 | 9.8 | |
| 6 days ago | 1 day ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | 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.
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.
optimas
Posts with mentions or reviews of optimas.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-08-31.
-
BoTorch – Bayesian Optimization in PyTorch
It's also very useful for simulation-based optimization. As an example, we use it extensively for the design of particle accelerators, where the simulations are typically expensive and need to run on supercomputers. We have built our own library[0] for enabling this, which in the end uses BoTorch (through Ax[1]) under the hood.
[0]: https://github.com/optimas-org/optimas
Ax
Posts with mentions or reviews of Ax.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-10.
-
Using Large Language Models for Hyperparameter Optimization, Zhang et al. 2023 [GPT-4 is quite good at finding the optimal hyperparameters for machine learning tasks]
Why not use a Bayesian optimization framework like Ax instead? https://ax.dev/
- BoTorch – Bayesian Optimization in PyTorch
- Did recent AI events change your life plans?
What are some alternatives?
When comparing optimas and Ax you can also consider the following projects:
botorch - Bayesian optimization in PyTorch
circuit_training
vortex-auv - Software for guidance, navigation and control for the Vortex AUVs. Purpose built for competing in AUV/ROV competitions.