Search Results for author:
Found 2 papers, 1 papers with code
Heavy Ball Neural Ordinary Differential Equations
We propose heavy ball neural ordinary differential equations (HBNODEs), leveraging the continuous limit of the classical momentum accelerated gradient descent, to improve neural ODEs (NODEs) training and inference.
FMMformer: Efficient and Flexible Transformer via Decomposed Near-field and Far-field Attention
For instance, FMMformers achieve an average classification accuracy of $60. 74\%$ over the five Long Range Arena tasks, which is significantly better than the standard transformer's average accuracy of $58. 70\%$.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
