botorch vs smt

botorch

Bayesian optimization in PyTorch (by pytorch)

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Source Code

botorch.org

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smt

Surrogate Modeling Toolbox (by SMTorg)

surrogate-models derivative Sampling mixture-of-experts multi-fidelity predictive-modeling Machine Learning

Source Code

smt.readthedocs.io

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botorch		smt
	Project
5	Mentions	1
2,949	Stars	621
1.5%	Growth	3.2%
9.4	Activity	8.6
5 days ago	Latest Commit	3 days ago
Jupyter Notebook	Language	Jupyter Notebook
MIT License	License	BSD 3-clause "New" or "Revised" 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.

botorch

Posts with mentions or reviews of botorch. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-06.

botorch VS SMT - a user suggested alternative
2 projects | 6 Dec 2023
BoTorch – Bayesian Optimization in PyTorch
1 project | /r/hypeurls | 2 Sep 2023

3 projects | news.ycombinator.com | 31 Aug 2023
[D] Uncertainty estimation with calibration set (with MC Dropout)
1 project | /r/MachineLearning | 4 Mar 2022

The true answer for this is modelling the problem bayesian in the first place using, for example, https://botorch.org/ and https://gpytorch.ai/.
Bayesian Optimization Book
3 projects | news.ycombinator.com | 14 Nov 2021

Yes, I'm using a binary outcome, since that's what I get from playing a game. To get probabilities I'd have to play a lot of games with the same settings/features/point and take the mean, but it seems that defeats the point of Bayesian optimization finding the best point to evaluate for each iteration.
The SPSA method seems to work quite well with binary outcomes. This is what I was trying to beat. Unfortunately I was never able to converge faster than SPSA (or even close to that) even increasing the number of samples.
I got some feedback form the botorch team back then: https://github.com/pytorch/botorch/issues/347#:~:text=thomas...

smt

Posts with mentions or reviews of smt. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-06.

botorch VS SMT - a user suggested alternative
2 projects | 6 Dec 2023

For unconstrained Bayesian Optimization

What are some alternatives?

When comparing botorch and smt you can also consider the following projects:

stat_rethinking_2022 - Statistical Rethinking course winter 2022

eve-sso - Eve Online Single Sign On (SSO)

Ax - Adaptive Experimentation Platform

AI-Hacktoberfest - Welcome to the Hacktoberfest Challenge for Artificial Intelligence / Machine Learning ! Today we will be assessing your skills to Predict Forest Fire Areas given its various parameters!

noisy-bayesian-optimization - Bayesian Optimization for very Noisy functions

ISLR-python - An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

optimas - Optimization at scale, powered by libEnsemble

eve-echoes-tools - Collection of tools helping in reverse engineering Eve Echoes

Z-S-Overview-Pack - Overview Pack for EVE Online

elinor-reloaded - Trading tool for Eve Online