Shengyu Zhu

According to our database, Shengyu Zhu authored at least 37 papers between 2013 and 2024.

Collaborative distances:

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

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

Causal Discovery by Kernel Deviance Measures with Heterogeneous Transforms.

Tim Tse, Zhitang Chen, Shengyu Zhu, Yue Liu

CoRR, 2024

2023

A Unified Framework for Layout Pattern Analysis With Deep Causal Estimation.

Ran Chen, Shoubo Hu, Zhitang Chen, Shengyu Zhu, Bei Yu, Pengyun Li, Cheng Chen, Yu Huang, Jianye Hao

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., April, 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

GFlowCausal: Generative Flow Networks for Causal Discovery.

Wenqian Li, Yinchuan Li, Shengyu Zhu, Yunfeng Shao, Jianye Hao, Yan Pang

CoRR, 2022

ZIN: When and How to Learn Invariance by Environment Inference?

Yong Lin, Shengyu Zhu, Peng Cui

CoRR, 2022

A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems.

Yan Lyu, Sunhao Dai, Peng Wu, Quanyu Dai, Yuhao Deng, Wenjie Hu, Zhenhua Dong, Jun Xu, Shengyu Zhu, Xiao-Hua Zhou

CoRR, 2022

Universality of parametric Coupling Flows over parametric diffeomorphisms.

Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, Zhijie Xu, Yongwei Chen

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

Reframed GES with a neural conditional dependence measure.

Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Masked Gradient-Based Causal Structure Learning.

Ignavier Ng, Shengyu Zhu, Zhuangyan Fang, Haoyang Li, Zhitang Chen, Jun Wang

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Para-CFlows: $C^k$-universal diffeomorphism approximators as superior neural surrogates.

Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, Zhijie Xu, Chen Yongwei

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

ZIN: When and How to Learn Invariance Without Environment Partition?

Yong Lin, Shengyu Zhu, Lu Tan, Peng Cui

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

RCANet: Root Cause Analysis via Latent Variable Interaction Modeling for Yield Improvement.

Xiaopeng Zhang, Shoubo Hu, Zhitang Chen, Shengyu Zhu, Evangeline F. Y. Young, Pengyun Li, Cheng Chen, Yu Huang, Jianye Hao

Proceedings of the IEEE International Test Conference, 2022

Out-of-distribution Generalization with Causal Invariant Transformations.

Ruoyu Wang, Mingyang Yi, Zhitang Chen, Shengyu Zhu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Asymptotically Optimal One- and Two-Sample Testing With Kernels.

Shengyu Zhu, Biao Chen, Zhitang Chen, Pengfei Yang

IEEE Trans. Inf. Theory, 2021

gCastle: A Python Toolbox for Causal Discovery.

Keli Zhang, Shengyu Zhu, Marcus Kalander, Ignavier Ng, Junjian Ye, Zhitang Chen, Lujia Pan

CoRR, 2021

Ordering-Based Causal Discovery with Reinforcement Learning.

Xiaoqiang Wang, Yali Du, Shengyu Zhu, Liangjun Ke, Zhitang Chen, Jianye Hao, Jun Wang

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2020

Causal Discovery with Reinforcement Learning.

Shengyu Zhu, Ignavier Ng, Zhitang Chen

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

A Graph Autoencoder Approach to Causal Structure Learning.

Ignavier Ng, Shengyu Zhu, Zhitang Chen, Zhuangyan Fang

CoRR, 2019

Masked Gradient-Based Causal Structure Learning.

Ignavier Ng, Zhuangyan Fang, Shengyu Zhu, Zhitang Chen

CoRR, 2019

Causal Discovery by Kernel Intrinsic Invariance Measure.

Zhitang Chen, Shengyu Zhu, Yue Liu, Tim Tse

CoRR, 2019

Causal Discovery with Reinforcement Learning.

Shengyu Zhu, Zhitang Chen

CoRR, 2019

Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit.

Shengyu Zhu, Biao Chen, Pengfei Yang, Zhitang Chen

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Distributed Detection in Ad Hoc Networks Through Quantized Consensus.

Shengyu Zhu, Biao Chen

IEEE Trans. Inf. Theory, 2018

Exponentially Consistent Kernel Two-Sample Tests.

Shengyu Zhu, Biao Chen, Zhitang Chen

CoRR, 2018

2017

Corrections to "Quantized Consensus by the ADMM: Probabilistic Versus Deterministic Quantizers".

Shengyu Zhu, Biao Chen

IEEE Trans. Signal Process., 2017

2016

Quantized Consensus by the ADMM: Probabilistic Versus Deterministic Quantizers.

Shengyu Zhu, Biao Chen

IEEE Trans. Signal Process., 2016

Distributed Detection in Ad Hoc Networks Through Quantized Consensus-Part II: Asymptotically Optimal Detection via One-Bit Communications.

Shengyu Zhu, Biao Chen

CoRR, 2016

Distributed average consensus with bounded quantization.

Shengyu Zhu, Biao Chen

Proceedings of the 17th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2016

Distributed detection over connected networks via one-bit quantizer.

Shengyu Zhu, Biao Chen

Proceedings of the IEEE International Symposium on Information Theory, 2016

Quantized consensus ADMM for multi-agent distributed optimization.

Shengyu Zhu, Mingyi Hong, Biao Chen

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015

Distributed average consensus with deterministic quantization: An ADMM approach.

Shengyu Zhu, Biao Chen

Proceedings of the 2015 IEEE Global Conference on Signal and Information Processing, 2015

2014

Decentralized Data Reduction With Quantization Constraints.

Ge Xu, Shengyu Zhu, Biao Chen

IEEE Trans. Signal Process., 2014

2013

Interactive distributed detection with conditionally independent observations.

Shengyu Zhu, Earnest Akofor, Biao Chen

Proceedings of the 2013 IEEE Wireless Communications and Networking Conference (WCNC), 2013

Data reduction in tandem fusion systems.

Shengyu Zhu, Biao Chen

Proceedings of the 2013 IEEE China Summit and International Conference on Signal and Information Processing, 2013

Are global sufficient statistics always sufficient: The impact of quantization on decentralized data reduction.

Shengyu Zhu, Ge Xu, Biao Chen

Proceedings of the 2013 Asilomar Conference on Signals, 2013