Cheby-KANs Dataset
Authors/Creators
Description
These are the codes and models used in our experiments regarding our submitted article “Cheby-KANs: Advanced Kolmogorov-Arnold Networks for Applying Geometric Deep Learning in Quantum Chemistry Applications”. The code is developed using python programming language. In our paper we hae
developed the B-spline based KANs with a more powerful and much faster polynomials “shifted-Chebyshev polynomials” of the first kind. Also, we integrated our new architecture with geometric deeplearning to predict quantum properties. This was done by modifying the famous Schnet model by using
our new model rather than the ordinary multi-layer-perceptrons. Attached are the files for the codes and the pretrained models.
We are using python for our experiments, and make sure to install the latest version of Pytorch and Pytorch-Geometric to be ble to load the pretrained models to reproduce the results.
Files
models.zip
Files
(549.6 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:e9704d710e0f1330ac5a0f26441cde12
|
549.6 MB | Preview Download |