Jim137/qkan
PyTorch implementation of QKAN "Quantum-inspired Kolmogorov-Arnold Network" https://arxiv.org/abs/2509.14026
This tool helps researchers and machine learning practitioners build and train "Quantum-inspired Kolmogorov-Arnold Networks" (QKANs). It takes raw data and model configuration to produce trained models that can fit functions, classify data, or generate new data. This is ideal for those exploring advanced neural network architectures, especially those interested in quantum computing's influence on AI.
Used by 1 other package. Available on PyPI.
Use this if you are a machine learning researcher or practitioner looking to implement and experiment with a novel quantum-inspired neural network architecture (QKANs) for tasks like function approximation or classification.
Not ideal if you are looking for a simple, off-the-shelf neural network solution without an interest in the underlying quantum-inspired activation functions or experimental AI research.
Stars
20
Forks
8
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 09, 2026
Commits (30d)
0
Dependencies
3
Reverse dependents
1
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Jim137/qkan"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
NVIDIAGameWorks/kaolin
A PyTorch Library for Accelerating 3D Deep Learning Research
lgy112112/ikan
ikan: many kan variants for every body
AntonioTepsich/Convolutional-KANs
This project extends the idea of the innovative architecture of Kolmogorov-Arnold Networks (KAN)...
Indoxer/LKAN
Variations of Kolmogorov-Arnold Networks
RomanBresson/KAGNN
This is the official repository for our paper KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning.