10 citations · 26 across the 10 of their papers we have counts for
10 papers
LEDA: Latent Semantic Distribution Alignment for Multi-domain Graph Pre-training
Lianze Shan, Jitao Zhao, Dongxiao He +3
Recent advances in generic large models, such as GPT and DeepSeek, have motivated the introduction of universality to graph pre-training, aiming to learn rich and generalizable kno…
Variety Is the Spice of Life: Detecting Misinformation with Dynamic Environmental Representations
Bing Wang, Ximing Li, Yiming Wang +4
The proliferation of misinformation across diverse social media platforms has drawn significant attention from both academic and industrial communities due to its detrimental effec…
Symbolic Foundation Regressor on Complex Networks
Weiting Liu, Jiaxu Cui, Jiao Hu +2
In science, we are interested not only in forecasting but also in understanding how predictions are made, specifically what the interpretable underlying model looks like. Data-driv…
Learning Interpretable Network Dynamics via Universal Neural Symbolic Regression
Jiao Hu, Jiaxu Cui, Bo Yang
Discovering governing equations of complex network dynamics is a fundamental challenge in contemporary science with rich data, which can uncover the mysterious patterns and mechani…
Learning Continuous Network Emerging Dynamics from Scarce Observations via Data-Adaptive Stochastic Processes
Jiaxu Cui, Bingyi Sun, Jiming Liu +1
Learning network dynamics from the empirical structure and spatio-temporal observation data is crucial to revealing the interaction mechanisms of complex networks in a wide range o…
Scalable Multiagent Driving Policies For Reducing Traffic Congestion
Jiaxun Cui, William Macke, Harel Yedidsion +2
Traffic congestion is a major challenge in modern urban settings. The industry-wide development of autonomous and automated vehicles (AVs) motivates the question of how can AVs con…
Deep Bayesian Optimization on Attributed Graphs
Jiaxu Cui, Bo Yang, Xia Hu
Attributed graphs, which contain rich contextual features beyond just network structure, are ubiquitous and have been observed to benefit various network analytics applications. Gr…
Learning Optimal Data Augmentation Policies via Bayesian Optimization for Image Classification Tasks
Chunxu Zhang, Jiaxu Cui, Bo Yang
In recent years, deep learning has achieved remarkable achievements in many fields, including computer vision, natural language processing, speech recognition and others. Adequate…
Deep Neural Architecture Search with Deep Graph Bayesian Optimization
Lizheng Ma, Jiaxu Cui, Bo Yang
Bayesian optimization (BO) is an effective method of finding the global optima of black-box functions. Recently BO has been applied to neural architecture search and shows better p…
Graph Bayesian Optimization: Algorithms, Evaluations and Applications
Jiaxu Cui, Bo Yang
Network structure optimization is a fundamental task in complex network analysis. However, almost all the research on Bayesian optimization is aimed at optimizing the objective fun…