Yingtao Luo

According to our database, Yingtao Luo authored at least 17 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

RMT-Net: Reject-Aware Multi-Task Network for Modeling Missing-Not-At-Random Data in Financial Credit Scoring.

Qiang Liu, Yingtao Luo, Shu Wu, Zhen Zhang, Xiangnan Yue, Hong Jin, Liang Wang

IEEE Trans. Knowl. Data Eng., July, 2023

Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning.

Jannik Deuschel, Caleb N. Ellington, Benjamin J. Lengerich, Yingtao Luo, Pascal Friederich, Eric P. Xing

CoRR, 2023

GSLB: The Graph Structure Learning Benchmark.

Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu

CoRR, 2023

GSLB: The Graph Structure Learning Benchmark.

Zhixun Li, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations.

Yingtao Luo, Qiang Liu, Yuntian Chen, Wenbo Hu, Tian Tian, Jun Zhu

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

AdaMCT: Adaptive Mixture of CNN-Transformer for Sequential Recommendation.

Juyong Jiang, Peiyan Zhang, Yingtao Luo, Chaozhuo Li, Jae Boum Kim, Kai Zhang, Senzhang Wang, Xing Xie, Sunghun Kim

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Improving Multi-Interest Network with Stable Learning.

Zhaocheng Liu, Yingtao Luo, Di Zeng, Qiang Liu, Daqing Chang, Dongying Kong, Zhi Chen

CoRR, 2022

AdaMCT: Adaptive Mixture of CNN-Transformer for Sequential Recommendation.

Juyong Jiang, Jae Boum Kim, Yingtao Luo, Kai Zhang, Sunghun Kim

CoRR, 2022

Learning Differential Operators for Interpretable Time Series Modeling.

Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Heterogeneous Graph Based Knowledge Tracing.

Yingtao Luo, Bing Xiao, Hua Jiang, Junliang Ma

Proceedings of the 11th International Conference on Educational and Information Technology, 2022

Deep Stable Representation Learning on Electronic Health Records.

Yingtao Luo, Zhaocheng Liu, Qiang Liu

Proceedings of the IEEE International Conference on Data Mining, 2022

2021

Sequential Recommendation with Bidirectional Chronological Augmentation of Transformer.

Juyong Jiang, Yingtao Luo, Jae Boum Kim, Kai Zhang, Sunghun Kim

CoRR, 2021

Any equation is a forest: Symbolic genetic algorithm for discovering open-form partial differential equations (SGA-PDE).

Yuntian Chen, Yingtao Luo, Qiang Liu, Hao Xu, Dongxiao Zhang

CoRR, 2021

KO-PDE: Kernel Optimized Discovery of Partial Differential Equations with Varying Coefficients.

Yingtao Luo, Qiang Liu, Yuntian Chen, Wenbo Hu, Jun Zhu

CoRR, 2021

STAN: Spatio-Temporal Attention Network for Next Location Recommendation.

Yingtao Luo, Qiang Liu, Zhaocheng Liu

Proceedings of the WWW '21: The Web Conference 2021, 2021

2020

Deep Spatial Learning with Molecular Vibration.

Ziyang Zhang, Yingtao Luo

CoRR, 2020

A Quantum-Inspired Probabilistic Model for the Inverse Design of Meta-Structures.

Yingtao Luo, Xuefeng Zhu

CoRR, 2020