no code implementations • 24 Feb 2024 • Haotian Xia, Zhengbang Yang, Yuqing Wang, Rhys Tracy, Yun Zhao, Dongdong Huang, Zezhi Chen, Yan Zhu, Yuan-Fang Wang, Weining Shen
A deep understanding of sports, a field rich in strategic and dynamic content, is crucial for advancing Natural Language Processing (NLP).
1 code implementation • 26 Sep 2023 • Haotian Xia, Rhys Tracy, Yun Zhao, Yuqing Wang, Yuan-Fang Wang, Weining Shen
Our frameworks combine setting ball trajectory recognition with a novel set trajectory classifier to generate comprehensive and advanced statistical data.
no code implementations • 22 Aug 2023 • Rhys Tracy, Haotian Xia, Alex Rasla, Yuan-Fang Wang, Ambuj Singh
Our results show that the use of GNNs with our graph encoding yields a much more advanced analysis of the data, which noticeably improves prediction results overall.
no code implementations • 28 Sep 2022 • Haotian Xia, Rhys Tracy, Yun Zhao, Erwan Fraisse, Yuan-Fang Wang, Linda Petzold
The second goal is to introduce a volleyball descriptive language to fully describe the rally processes in the games and apply the language to our dataset.
no code implementations • 1 Oct 2021 • Yun Zhao, Yuqing Wang, Junfeng Liu, Haotian Xia, Zhenni Xu, Qinghang Hong, Zhiyang Zhou, Linda Petzold
In this paper, we perform quantitative analysis of COVID-19 forecasting of confirmed cases and deaths across different regions in the United States with different forecasting horizons, and evaluate the relative impacts of the following three dimensions on the predictive performance (improvement and variation) through different evaluation metrics: model selection, hyperparameter tuning, and the length of time series required for training.