The rapid accumulation of protein sequence data, coupled with the slow pace of experimental annotations, creates a critical need for computational methods to predict protein functions. Existing models ...

Abstract: This paper proposes a family of Aligned Entropic Graph Kernels (AEGK) for graph classification, based on the Averaged Mixing Matrix (AMM) of Continuous-time Quantum Walks (CTQWs).

Abstract: Deep learning (DL) greatly enhances cyber anomaly detection capabilities through effective statistical network characteristic. However, previous methods have not fully addressed two ...

This repository contains the official PyTorch implementation for the CVPR 2024 Highlight paper titled "Latent Modulated Function for Computational Optimal Continuous Image Representation" by Zongyao ...