Yangbo He

According to our database, Yangbo He authored at least 15 papers between 2012 and 2024.

Collaborative distances:

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

2024

On Low-Rank Directed Acyclic Graphs and Causal Structure Learning.

Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He

IEEE Trans. Neural Networks Learn. Syst., April, 2024

2023

Causal discovery of 1-factor measurement models in linear latent variable models with arbitrary noise distributions.

Feng Xie, Yan Zeng, Zhengming Chen, Yangbo He, Zhi Geng, Kun Zhang

Neurocomputing, March, 2023

Conditional counterfactual causal effect for individual attribution.

Ruiqi Zhao, Lei Zhang, Shengyu Zhu, Zitong Lu, Zhenhua Dong, Chaoliang Zhang, Jun Xu, Zhi Geng, Yangbo He

Proceedings of the Uncertainty in Artificial Intelligence, 2023

2022

Testability of Instrumental Variables in Linear Non-Gaussian Acyclic Causal Models.

Feng Xie, Yangbo He, Zhi Geng, Zhengming Chen, Ru Hou, Kun Zhang

Entropy, 2022

On the Representation of Causal Background Knowledge and its Applications in Causal Inference.

Zhuangyan Fang, Ruiqi Zhao, Yue Liu, Yangbo He

CoRR, 2022

A local method for identifying causal relations under Markov equivalence.

Zhuangyan Fang, Yue Liu, Zhi Geng, Shengyu Zhu, Yangbo He

Artif. Intell., 2022

Identification of Linear Non-Gaussian Latent Hierarchical Structure.

Feng Xie, Biwei Huang, Zhengming Chen, Yangbo He, Zhi Geng, Kun Zhang

Proceedings of the International Conference on Machine Learning, 2022

Performance of Deep Reinforcement Learning for High Frequency Market Making on Actual Tick Data.

Ziyi Xu, Xue Cheng, Yangbo He

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021

A Local Method for Identifying Causal Relations under Markov Equivalence.

Zhuangyan Fang, Yue Liu, Zhi Geng, Yangbo He

CoRR, 2021

2020

Local Causal Network Learning for Finding Pairs of Total and Direct Effects.

Yue Liu, Zhuangyan Fang, Yangbo He, Zhi Geng, Chunchen Liu

J. Mach. Learn. Res., 2020

Collapsible IDA: Collapsing Parental Sets for Locally Estimating Possible Causal Effects.

Yue Liu, Zhuangyan Fang, Yangbo He, Zhi Geng

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

IDA with Background Knowledge.

Zhuangyan Fang, Yangbo He

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2016

Formulas for Counting the Sizes of Markov Equivalence Classes of Directed Acyclic Graphs.

Yangbo He, Bin Yu

CoRR, 2016

2015

Counting and exploring sizes of Markov equivalence classes of directed acyclic graphs.

Yangbo He, Jinzhu Jia, Bin Yu

J. Mach. Learn. Res., 2015

2012

Reversible MCMC on Markov equivalence classes of sparse directed acyclic graphs

Yangbo He, Jinzhu Jia, Bin Yu

CoRR, 2012