rssalessio/PytorchRBFLayer
Pytorch RBF Layer implements a radial basis function layer in Pytorch. Radial Basis networks can be used to approximate functions.
This is a tool for machine learning practitioners and researchers working with neural networks. It helps create Radial Basis Function (RBF) layers within PyTorch models to approximate complex functions or perform classification. You input your data and define the RBF layer's parameters, and it outputs predictions or classifications.
Use this if you need to incorporate Radial Basis Function networks into your PyTorch machine learning models for tasks like function approximation or classification.
Not ideal if you are not working with PyTorch or are looking for a complete, out-of-the-box RBF network solution rather than a customizable layer.
Stars
52
Forks
14
Language
Python
License
MIT
Category
Last pushed
Nov 09, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/rssalessio/PytorchRBFLayer"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
sbi-dev/sbi
sbi is a Python package for simulation-based inference, designed to meet the needs of both...
SMTorg/smt
Surrogate Modeling Toolbox
reservoirpy/reservoirpy
A simple and flexible code for Reservoir Computing architectures like Echo State Networks
GPflow/GPflow
Gaussian processes in TensorFlow
dswah/pyGAM
[CONTRIBUTORS WELCOME] Generalized Additive Models in Python