In today’s rapidly evolving landscape, integrating automated systems into various aspects of daily tasks is a primary objective for both industry and academia. …
Graph Neural Networks (GNNs) have proven highly effective in graph-related tasks, including Traffic Modeling, Learning Physical Simulations, Protein Modeling, and Large-scale Recommender Systems. …
In this lab, we provide a hands-on experience to help users develop and evaluate novel Graph Counterfactual Explanation (GCE) methods using a simple and modular framework, GRETEL. …
Graph Neural Networks (GNNs) have proven highly effective in graph-related tasks, including Traffic Modeling, Learning Physical Simulations, Protein Modeling, and Large-scale Recommender Systems. …