Inspired by the latest progress of deep learning, we propose a dynamic graph fusion network (DGFN) architecture to tackle the topology and line parameter joint identification problem.

GNAQ is a novel quantization framework enhancing GNN efficiency and accuracy in Top-K recommendation. GNAQ leverages graph structure via node-aware parameter sharing, dynamic quantization steps, a ...

The graph below shows the total number of publications each year in Dynamic Modeling and Parameter Identification for Robotics.

Spectro-Graph Mamba++ UltraDeep (SGM-UD): 162M-parameter deep learning architecture for whole-slide histopathology image classification combining spectral decomposition, large-kernel convolutions, ...

Tableau 2020.1 is the latest update driven by customers’ input in the online Tableau Community Forums, adding new features requested by Tableau customers and increased flexibility for administrators.

To address the issue of recycling efficiency, a knowledge graph-based dynamic differential evolution algorithm (DE-KG) is proposed. Knowledge graphs are constructed for different delivery scenarios to ...