Abstract: Neural operators have emerged as a powerful tool for learning mappings between function spaces, particularly for solving partial differential equations (PDEs). This study introduces a novel ...

Our demo for skeleton based action recognition: ST-GCN is able to exploit local pattern and correlation from human skeletons. Below figures show the neural response magnitude of each node in the last ...

Abstract: Graph neural networks (GNNs) excel in graph representation learning by integrating graph structure and node features. Existing GNNs, unfortunately, fail to account for the uncertainty of ...