opthub-org/pytorch-bsf
PyTorch implementation of Bezier simplex fitting
When you have complex, high-dimensional data points and need to understand the smooth underlying structure or optimal trade-offs, this tool helps. You provide your observations (like design parameters and their corresponding performance metrics), and it outputs a smooth, flexible surface that represents the relationship between them. This is ideal for scientists, engineers, or researchers working with multi-objective optimization results or interpolating scattered experimental data.
Available on PyPI.
Use this if you need to fit a smooth, high-dimensional surface to complex data, especially for visualizing Pareto fronts in multi-objective optimization or interpolating scattered observations.
Not ideal if your data relationships are simple and low-dimensional, or if you require discrete, rather than smooth, representations.
Stars
12
Forks
4
Language
Python
License
MIT
Category
Last pushed
Mar 17, 2026
Commits (30d)
0
Dependencies
8
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