10 citations · 10 across the 6 of their papers we have counts for
5 papers · 1 filter
Beauty in the Eye of AI: Aligning LLMs and Vision Models with Human Aesthetics in Network Visualization
Peng Zhang, Xuefeng Li, Xiaoqi Wang +2
Network visualization has traditionally relied on heuristic metrics, such as stress, under the assumption that optimizing them leads to aesthetic and informative layouts. However,…
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction
Ziwei Li, Xiaoqi Wang, Hong-You Chen +2
Federated learning (FL) has rapidly evolved as a promising paradigm that enables collaborative model training across distributed participants without exchanging their local data. D…
GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
Xiaoqi Wang, Han-Wei Shen
Recently, Graph Neural Networks (GNNs) have significantly advanced the performance of machine learning tasks on graphs. However, this technological breakthrough makes people wonder…
SmartGD: A GAN-Based Graph Drawing Framework for Diverse Aesthetic Goals
Xiaoqi Wang, Kevin Yen, Yifan Hu +1
While a multitude of studies have been conducted on graph drawing, many existing methods only focus on optimizing a single aesthetic aspect of graph layouts, which can lead to sub-…
DeepGD: A Deep Learning Framework for Graph Drawing Using GNN
Xiaoqi Wang, Kevin Yen, Yifan Hu +1
In the past decades, many graph drawing techniques have been proposed for generating aesthetically pleasing graph layouts. However, it remains a challenging task since different la…