BayesOpt
VTMOP
| BayesOpt | VTMOP | |
|---|---|---|
| 1 | 1 | |
| 379 | 1 | |
| - | - | |
| 1.1 | 10.0 | |
| about 1 year ago | over 1 year ago | |
| C++ | Fortran | |
| GNU Affero General Public License v3.0 | MIT License |
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BayesOpt
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The Evolutionary Computation Methods No One Should Use
Very interesting to see how wide spread this is. Stumbled upon it myself by accident when comparing my algorithm to a popular Bayesian optimisation algorithm (https://github.com/rmcantin/bayesopt). Almost every run it would sample the exact centre of the optimisation space. At first I was blown away by the performance until I found it suspicious that the precise optimum was found so often. Shifting the optimum away from the centre greatly reduced the algorithms performance.
VTMOP
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The Evolutionary Computation Methods No One Should Use
I wrote a modified DTLZ set in Fortran while evaluating the methods for my PhD thesis (https://github.com/vtopt/VTMOP) so that the solutions will be slightly offset (I think by like 0.2)
What are some alternatives?
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Fortran-MOOC - Material related to the PRACE MOOC on Fortran programming
tensorflow - An Open Source Machine Learning Framework for Everyone
stdlib - Fortran Standard Library
Recast/Detour - Industry-standard navigation-mesh toolset for games
WRF - The official repository for the Weather Research and Forecasting (WRF) model
AI-Toolbox - A C++ framework for MDPs and POMDPs with Python bindings
fpm - Fortran Package Manager (fpm)
tiny-cnn - header only, dependency-free deep learning framework in C++14
parmoo - Python library for parallel multiobjective simulation optimization
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
btsk - Behavior Tree Starter Kit