Surrogate modeling and optimization for scientific machine learning (SciML)
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Updated
Jul 24, 2024 - Julia
Surrogate modeling and optimization for scientific machine learning (SciML)
Official and maintained implementation of the paper "Differentiable JPEG: The Devil is in the Details" [WACV 2024].
A Julia package for generating timeseries surrogates
This is our standard library for nonlinear analysis. Many of these functions are the same we use in our services. We do have additional methods that are not public but could be made available in a future release. If you are interested in learning more, attending our workshops or webinars or using our data analysis services please contact bmchnon…
A modular code for teaching Surrogate Modeling-Based Optimization
In this repository I publish the python code, that was part of my master thesis. The thesis can be found here, however its in German though, sry. :/
A service that provides archive-aware oEmbed-compatible embeddable surrogates (social cards, thumbnails, etc.) for archived web pages (mementos).
Probabilistic Response mOdel Fitting with Interactive Tools
Surrogate model library for Derivative-Free Optimization
Create a surrogate ANN/GBR/GPR/SVR model for regression of nuclear reactor power distribution
Neural-networks based sleep staging in tensorflow, and evalutation with Fourier-transform based surrogates.
GPT3-enabled surrogate functions in C++
A complete expected improvement criterion for Gaussian process assisted highly constrained expensive optimization
Last Presentation from the prof !
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