Graph Neural Networks (GNNs) are a powerful tool for handling structured...
Polynomial regression is widely used and can help to express nonlinear
p...
As deep learning models grow, sparsity is becoming an increasingly criti...
With the application of machine learning to security-critical and sensit...
Rapid progress in deep learning is leading to a diverse set of quickly
c...
This paper presents a novel approach for constructing neural networks wh...
Transformers have become widely used for language modeling and sequence
...
This paper discusses an approach for incorporating prior physical knowle...
This paper discusses an approach for incorporating prior physical knowle...
The connection of Taylor maps and polynomial neural networks (PNN) to so...
The coincidence between polynomial neural networks and matrix Lie maps i...
In the article, we discuss the architecture of the polynomial neural net...