Junji Jiang

Orcid: 0000-0001-9675-0903

According to our database1, Junji Jiang authored at least 13 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2024
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning.
ACM Comput. Surv., July, 2024

Deep graph representation learning influence maximization with accelerated inference.
Neural Networks, 2024

Quantifying uncertainty in graph neural network explanations.
Frontiers Big Data, 2024

Team formation in large organizations: A deep reinforcement learning approach.
Decis. Support Syst., 2024

2023
Forecasting movements of stock time series based on hidden state guided deep learning approach.
Inf. Process. Manag., May, 2023

Deep Graph Representation Learning and Optimization for Influence Maximization.
CoRR, 2023

KMF: Knowledge-Aware Multi-Faceted Representation Learning for Zero-Shot Node Classification.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Deep Graph Representation Learning and Optimization for Influence Maximization.
Proceedings of the International Conference on Machine Learning, 2023

Knowledge-Aware Cross-Semantic Alignment for Domain-Level Zero-Shot Recommendation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
An Invertible Graph Diffusion Neural Network for Source Localization.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

DeepGAR: Deep Graph Learning for Analogical Reasoning.
Proceedings of the IEEE International Conference on Data Mining, 2022

2021
GraphGT: Machine Learning Datasets for Graph Generation and Transformation.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021


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