Dantong Yu

Ajim Uddiin, Xinyuan Tao, Dantong Yu. 2023. “Attention based dynamic graph neural network for asset pricing..” Global finance journal, vol. 58.

Ajim Uddiin, Xinyuan Tao, Dantong Yu. 2023. “Attention Based Dynamic Graph Neural Network for Asset Pricing.” Global Finance Journal, vol. 58, no. November 2023.

Uras Varolgunes, Shibo Yao, Yao Ma, Dantong Yu. 2023. “Embedding Imputation With Self-Supervised Graph Neural Networks.” IEEE Access, vol. 11, pp. 70610--70620.

Mengchuan Fu, Dantong Yu, Dan Zhou. 2023. “Secret Recipe of IPO survival: ESG disclosure and performance.” Financial Markets, Institutions & Instruments, vol. 32, no. 1, pp. 3-19.

Ajim Uddiin, Xinyuan Tao, Chia-Ching Chou, Dantong Yu. 2022. “Are missing values important for earnings forecasts? A machine learning perspective.” Quantitative Finance , vol. 22, no. 6, pp. 1113-1132 .

Ajim Uddiin, Xinyuan Tao, C C Chou, Dantong Yu. 2022. “Are missing values important for earnings forecast? a machine learning perspective..” Quantitative finance, vol. 22, no. 6, pp. 1113-1132.

Ajim Uddiin, Xinyuan Tao, Chia Ching Chou, Dantong Yu. 2022. “Are missing values important for earnings forecasts? A machine learning perspective.” Quantitative Finance, vol. 22, no. 6, pp. 1113-1132.

Xinyue Ye, Wenbo Wang, Xiaoqi Zhang, Zhenlong Li, Dantong Yu, Jiaxin Du, Zhihui Chen. 2021. “Reconstructing spatial information diffusion networks with heterogeneous agents and text contents.” Trans. GIS, vol. 25, no. 4, pp. 1654--1673.

Ajim Uddiin, Dantong Yu. 2020. “Latent factor model for asset pricing.” Journal of Behavioral and Experimental Finance, vol. 27, pp. 100353.

Ajim Uddiin, Dantong Yu. 2020. “Latent factor model for asset pricing.” Journal of Behavioral and Experimental Finance, vol. 27.

A P Arkin, R W Cottingham, C S Henry, N L Harris, R L Stevens, S Maslov, P Dehal, D Ware, F Perez, S Canon, M W Sneddon, M L Henderson, W J Riehl, D Murphy-Olson, S Y Chan, R T Kamimura, S Kumari, M M Drake, T S Brettin, E M Glass, D Chivian, D Gunter, D J Weston, B H Allen, J Baumohl, A A Best, B Bowen, S E Brenner, C C Bun, J M Chandonia, J M Chia, R Colasanti, N Conrad, J J Davis, B H Davison, M DeJongh, S Devoid, E Dietrich, I Dubchak, J N Edirisinghe, G Fang, J P Faria, P M Frybarger, W Gerlach, M Gerstein, A Greiner, J Gurtowski, H L Haun, F He, R Jain, M P Joachimiak, K P Keegan, S Kondo, V Kumar, M L Land, F Meyer, M Mills, P S Novichkov, T Oh, G J Olsen, R Olson, B Parrello, S Pasternak, E Pearson, S S Poon, G A Price, S Ramakrishnan, P Ranjan, P C Ronald, M C Schatz, Seaver SMD, M Shukla, R A Sutormin, M H Syed, J Thomason, N L Tintle, D Wang, F Xia, H Yoo, S Yoo, Dantong Yu. 2018. “KBase: The United States Department of Energy Systems Biology Knowledgebase..” Nature biotechnology, vol. 36, no. 7, pp. 566-569.

Tan Li, Yufei Ren, Dantong Yu, Shudong Jin. 2017. “RAMSYS: Resource-Aware Asynchronous Data Transfer with Multicore SYStems.” IEEE Transactions on Parallel and Distributed Systems, vol. 28, no. 5, pp. 1430-1444.

Zhenzhou Peng, Dantong Yu, Dong Huang, John Heiser, Shinjae Yoo, Paul Kalb. 2015. “3D cloud detection and tracking system for solar forecast using multiple sky imagers.” Solar Energy, vol. 118, pp. 496-519.

“End-to-End Pipeline for Trigger Detection on Hit and Track Graphs”
AAAI Press, September 2023.

“Core Matrix Regression and Prediction with Regularization”
ACM, 2022.

“Machine Learning for Earnings Prediction: A Nonlinear Tensor Approach for Data Integration and Completion”
ACM, 2022.

“Temporal Bipartite Graph Neural Networks for Bond Prediction”
ACM, 2022.

“Machine Learning for Earnings Prediction: A Nonlinear Tensor Approach for Data Integration and Completion”
3th ACM International Conference on AI in Finance: ICAIF'22, November 2022.

“Temporal Bipartite Graph Neural Networks for Bond Prediction”
3th ACM International Conference on AI in Finance: ICAIF'22, November 2022.

“Core Matrix Regression and Prediction with Regularization”
November 2022.

“Machine Learning for Earnings Prediction: A Nonlinear Tensor Approach for Data Integration and Completion”
November 2022.

“Temporal Bipartite Graph Neural Networks for Bond Prediction”
November 2022.

“Trigger Detection for the sPHENIX Experiment via Bipartite Graph Networks with Set Transformer”
Springer, September 2022.

“Attention Based Dynamic Graph Learning Framework for Asset Pricing”
ACM, 2021.

“Perturbing Eigenvalues with Residual Learning in Graph Convolutional Neural Networks”
PMLR, 2021.

“Attention Based Dynamic Graph Learning Framework for Asset Pricing”
30th ACM International Conference on Information & Knowledge Management, CIKM-2021, October (4th Quarter/Autumn) 2021.

“Nonlinear Tensor Completion Using Domain Knowledge: An Application in Analysts' Earnings Forecast”
IEEE, 2020.

“Design and performance evaluation of NUMA-aware RDMA-based end-to-end data transfer systems”
ACM, November 2013.