Are global sufficient statistics always sufficient: The impact of quantization on decentralized data reduction. - Shengyu Zhu 001; Ge Xu; Biao Chen 001 (ACSSC, 2013)

Data reduction in tandem fusion systems. - Shengyu Zhu 001; Biao Chen 001 (ChinaSIP, 2013)

Interactive distributed detection with conditionally independent observations. - Shengyu Zhu 001; Earnest Akofor; Biao Chen 001 (WCNC, 2013)

Decentralized Data Reduction With Quantization Constraints. - Ge Xu; Shengyu Zhu 001; Biao Chen 001 (IEEE Trans. Signal Process., 2014)

Distributed average consensus with deterministic quantization: An ADMM approach. - Shengyu Zhu 001; Biao Chen 001 (GlobalSIP, 2015)

Quantized consensus ADMM for multi-agent distributed optimization. - Shengyu Zhu 001; Mingyi Hong 001; Biao Chen 001 (ICASSP, 2016)

Distributed detection over connected networks via one-bit quantizer. - Shengyu Zhu 001; Biao Chen 001 (ISIT, 2016)

Distributed average consensus with bounded quantization. - Shengyu Zhu 001; Biao Chen 001 (SPAWC, 2016)

Distributed Detection in Ad Hoc Networks Through Quantized Consensus-Part II: Asymptotically Optimal Detection via One-Bit Communications. - Shengyu Zhu 001; Biao Chen 001 (CoRR, 2016)

Quantized Consensus by the ADMM: Probabilistic Versus Deterministic Quantizers. - Shengyu Zhu 001; Biao Chen 001 (IEEE Trans. Signal Process., 2016)

Corrections to "Quantized Consensus by the ADMM: Probabilistic Versus Deterministic Quantizers". - Shengyu Zhu 001; Biao Chen 001 (IEEE Trans. Signal Process., 2017)

Exponentially Consistent Kernel Two-Sample Tests. - Shengyu Zhu 001; Biao Chen 001; Zhitang Chen (CoRR, 2018)

Distributed Detection in Ad Hoc Networks Through Quantized Consensus. - Shengyu Zhu 001; Biao Chen 001 (IEEE Trans. Inf. Theory, 2018)

Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit. - Shengyu Zhu 001; Biao Chen 001; Pengfei Yang 003; Zhitang Chen (AISTATS, 2019)

Causal Discovery with Reinforcement Learning. - Shengyu Zhu 001; Zhitang Chen (CoRR, 2019)

Causal Discovery by Kernel Intrinsic Invariance Measure. - Zhitang Chen; Shengyu Zhu 001; Yue Liu; Tim Tse (CoRR, 2019)

Masked Gradient-Based Causal Structure Learning. - Ignavier Ng; Zhuangyan Fang; Shengyu Zhu 001; Zhitang Chen (CoRR, 2019)

A Graph Autoencoder Approach to Causal Structure Learning. - Ignavier Ng; Shengyu Zhu 001; Zhitang Chen; Zhuangyan Fang (CoRR, 2019)

Causal Discovery with Reinforcement Learning. - Shengyu Zhu 001; Ignavier Ng; Zhitang Chen (ICLR, 2020)

Ordering-Based Causal Discovery with Reinforcement Learning. - Xiaoqiang Wang 003; Yali Du 001; Shengyu Zhu 001; Liangjun Ke; Zhitang Chen; Jianye Hao; Jun Wang 012 (IJCAI, 2021)

gCastle: A Python Toolbox for Causal Discovery. - Keli Zhang; Shengyu Zhu 001; Marcus Kalander; Ignavier Ng; Junjian Ye; Zhitang Chen; Lujia Pan (CoRR, 2021)

Asymptotically Optimal One- and Two-Sample Testing With Kernels. - Shengyu Zhu 001; Biao Chen 001; Zhitang Chen; Pengfei Yang 003 (IEEE Trans. Inf. Theory, 2021)

Out-of-distribution Generalization with Causal Invariant Transformations. - Ruoyu Wang 016; Mingyang Yi; Zhitang Chen; Shengyu Zhu 001 (CVPR, 2022)

RCANet: Root Cause Analysis via Latent Variable Interaction Modeling for Yield Improvement. - Xiaopeng Zhang 009; Shoubo Hu; Zhitang Chen; Shengyu Zhu 001; Evangeline F. Y. Young; Pengyun Li; Cheng Chen; Yu Huang 005; Jianye Hao (ITC, 2022)

ZIN: When and How to Learn Invariance Without Environment Partition? - Yong Lin; Shengyu Zhu 001; Lu Tan; Peng Cui 001 (NeurIPS, 2022)

Para-CFlows: $C^k$-universal diffeomorphism approximators as superior neural surrogates. - Junlong Lyu; Zhitang Chen; Chang Feng; Wenjing Cun; Shengyu Zhu 001; Yanhui Geng; Zhijie Xu; Chen Yongwei (NeurIPS, 2022)

Masked Gradient-Based Causal Structure Learning. - Ignavier Ng; Shengyu Zhu 001; Zhuangyan Fang; Haoyang Li 002; Zhitang Chen; Jun Wang 012 (SDM, 2022)

Reframed GES with a neural conditional dependence measure. - Xinwei Shen 002; Shengyu Zhu 001; Jiji Zhang; Shoubo Hu; Zhitang Chen (UAI, 2022)

A local method for identifying causal relations under Markov equivalence. - Zhuangyan Fang; Yue Liu; Zhi Geng; Shengyu Zhu 001; Yangbo He (Artif. Intell., 2022)

Universality of parametric Coupling Flows over parametric diffeomorphisms. - Junlong Lyu; Zhitang Chen; Chang Feng; Wenjing Cun; Shengyu Zhu 001; Yanhui Geng; Zhijie Xu; Yongwei Chen (CoRR, 2022)

A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems. - Yan Lyu; Sunhao Dai; Peng Wu 012; Quanyu Dai; Yuhao Deng; Wenjie Hu; Zhenhua Dong; Jun Xu 001; Shengyu Zhu 001; Xiao-Hua Zhou (CoRR, 2022)

ZIN: When and How to Learn Invariance by Environment Inference? - Yong Lin; Shengyu Zhu 001; Peng Cui 001 (CoRR, 2022)

GFlowCausal: Generative Flow Networks for Causal Discovery. - Wenqian Li; Yinchuan Li; Shengyu Zhu 001; Yunfeng Shao 001; Jianye Hao; Yan Pang (CoRR, 2022)

Provably Invariant Learning without Domain Information. - Xiaoyu Tan; Lin Yong; Shengyu Zhu 001; Chao Qu; Xihe Qiu; Yinghui Xu; Peng Cui 001; Yuan Qi 001 (ICML, 2023)

Conditional counterfactual causal effect for individual attribution. - Ruiqi Zhao; Lei Zhang; Shengyu Zhu 001; Zitong Lu; Zhenhua Dong; Chaoliang Zhang; Jun Xu 001; Zhi Geng; Yangbo He (UAI, 2023)

A Unified Framework for Layout Pattern Analysis With Deep Causal Estimation. - Ran Chen 001; Shoubo Hu; Zhitang Chen; Shengyu Zhu 001; Bei Yu 001; Pengyun Li; Cheng Chen; Yu Huang 005; Jianye Hao (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

Causal Discovery by Kernel Deviance Measures with Heterogeneous Transforms. - Tim Tse; Zhitang Chen; Shengyu Zhu 001; Yue Liu (CoRR, 2024)

On Low-Rank Directed Acyclic Graphs and Causal Structure Learning. - Zhuangyan Fang; Shengyu Zhu 001; Jiji Zhang; Yue Liu; Zhitang Chen; Yangbo He (IEEE Trans. Neural Networks Learn. Syst., 2024)

WToE: Learning When to Explore in Multiagent Reinforcement Learning. - Shaokang Dong; Hangyu Mao; Shangdong Yang; Shengyu Zhu 001; Wenbin Li 006; Jianye Hao; Yang Gao 001 (IEEE Trans. Cybern., 2024)

A Simple DropConnect Approach to Transfer-based Targeted Attack. - Tongrui Su; Qingbin Li; Shengyu Zhu 001; Wei Chen; Xueqi Cheng (CoRR, 2025)