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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About Me
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Posts
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Blog Post number 4
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Blog Post number 1
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portfolio
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publications
面向交通拥堵预测的可解释性时空分析方法
Published in China National Intellectual Property Administration, 2022
The invention discloses an interpretable spatio-temporal analysis method for traffic congestion prediction, which extracts the key features causing congestion events and the deep connection between roads from the interpretation. Traditional data mining methods often explore the correlation between traffic spatio-temporal data from the statistical point of view, and it is difficult to fully reveal the deep connection and key factors of traffic congestion. Therefore, the invention proposes a spati…
Recommended citation: 关佶红，孔令百，杨涵晨，李文根，张毅超. 面向交通拥堵预测的可解释性时空分析方法, 202211094177.3, 2022/09/08 https://lingbai-kong.github.io/files/面向交通拥堵预测的可解释性时空分析方法.pdf
Towards GNN-based Interpretable Traffic Prediction Framework and Performance
Published in Under Review, 2023
Nowadays, with the increasing traffic congestion problems in metropolises, traffic prediction plays an essential role in intelligent traffic systems. Notably, various deep learning models, especially graph neural networks (GNNs), achieve state-of-the-art performance in traffic prediction tasks but lack interpretability. To interpret the critical information abstracted by traffic prediction models, we proposed a universal framework termed Traffexplainer towards GNN-based interpretable traffic pre…
Recommended citation: Under Review
CauseFormer: An Interpretable Transformer for Temporal Causal Discovery
Published in Under Review, 2023
Temporal causal discovery has become an effective technique to reveal the internal causality of time series. However, most existing deep learning-based causal discovery methods only capture causal relations by analyzing the parameters of some components in the model, e.g., attention weights and convolution weights, which is a local-level mapping process from the parameters to the causality and fails to investigate the structure of the whole model to discover the causality. To facilitate the glob…
Recommended citation: Under Review
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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