Shengyu Zhu - RankMe

50 papers A* 6A 6B 2Misc 2Journal 31Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Simple DropConnect Approach to Transfer-based Targeted Attack. CoRR Tongrui Su, Qingbin Li, Shengyu Zhu, Wei Chen, Xueqi Cheng
2025	J	`jnl`	Speculative Safety-Aware Decoding. CoRR Xuekang Wang, Shengyu Zhu, Xueqi Cheng
2024	J	`jnl`	Causal Discovery by Kernel Deviance Measures with Heterogeneous Transforms. CoRR Tim Tse, Zhitang Chen, Shengyu Zhu, Yue Liu
2024	J	`jnl`	On Low-Rank Directed Acyclic Graphs and Causal Structure Learning. IEEE Trans. Neural Networks Learn. Syst. Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He
2024	J	`jnl`	WToE: Learning When to Explore in Multiagent Reinforcement Learning. IEEE Trans. Cybern. Shaokang Dong, Hangyu Mao, Shangdong Yang, Shengyu Zhu, Wenbin Li, Jianye Hao, Yang Gao
2023	J	`jnl`	A Unified Framework for Layout Pattern Analysis With Deep Causal Estimation. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Ran Chen, Shoubo Hu, Zhitang Chen, Shengyu Zhu, Bei Yu, Pengyun Li, Cheng Chen, Yu Huang, Jianye Hao
2023	A	`conf`	Conditional counterfactual causal effect for individual attribution. UAI Ruiqi Zhao, Lei Zhang, Shengyu Zhu, Zitong Lu, Zhenhua Dong, Chaoliang Zhang, Jun Xu, Zhi Geng, Yangbo He
2023	A*	`conf`	Provably Invariant Learning without Domain Information. ICML Xiaoyu Tan, Lin Yong, Shengyu Zhu, Chao Qu, Xihe Qiu, Yinghui Xu, Peng Cui, Yuan Qi
2022	J	`jnl`	A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems. CoRR Yan Lyu, Sunhao Dai, Peng Wu, Quanyu Dai, Yuhao Deng, Wenjie Hu, Zhenhua Dong, Jun Xu, Shengyu Zhu, Xiao-Hua Zhou
2022	J	`jnl`	A local method for identifying causal relations under Markov equivalence. Artif. Intell. Zhuangyan Fang, Yue Liu, Zhi Geng, Shengyu Zhu, Yangbo He
2022	J	`jnl`	GFlowCausal: Generative Flow Networks for Causal Discovery. CoRR Wenqian Li, Yinchuan Li, Shengyu Zhu, Yunfeng Shao, Jianye Hao, Yan Pang
2022	A	`conf`	Masked Gradient-Based Causal Structure Learning. SDM Ignavier Ng, Shengyu Zhu, Zhuangyan Fang, Haoyang Li, Zhitang Chen, Jun Wang
2022	A*	`conf`	Out-of-distribution Generalization with Causal Invariant Transformations. CVPR Ruoyu Wang, Mingyang Yi, Zhitang Chen, Shengyu Zhu
2022	J	`jnl`	Out-of-distribution Generalization with Causal Invariant Transformations. CoRR Ruoyu Wang, Mingyang Yi, Zhitang Chen, Shengyu Zhu
2022	A*	`conf`	Para-CFlows: $C^k$-universal diffeomorphism approximators as superior neural surrogates. NeurIPS Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, Zhijie Xu, Chen Yongwei
2022	A	`conf`	RCANet: Root Cause Analysis via Latent Variable Interaction Modeling for Yield Improvement. ITC Xiaopeng Zhang, Shoubo Hu, Zhitang Chen, Shengyu Zhu, Evangeline F. Y. Young, Pengyun Li, Cheng Chen, Yu Huang, Jianye Hao
2022	J	`jnl`	Reframed GES with a Neural Conditional Dependence Measure. CoRR Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen
2022	A	`conf`	Reframed GES with a neural conditional dependence measure. UAI Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen
2022	J	`jnl`	Universality of parametric Coupling Flows over parametric diffeomorphisms. CoRR Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, Zhijie Xu, Yongwei Chen
2022	A*	`conf`	ZIN: When and How to Learn Invariance Without Environment Partition? NeurIPS Yong Lin, Shengyu Zhu, Lu Tan, Peng Cui
2022	J	`jnl`	ZIN: When and How to Learn Invariance by Environment Inference? CoRR Yong Lin, Shengyu Zhu, Peng Cui
2021	A	`conf`	A Unified Framework for Layout Pattern Analysis with Deep Causal Estimation. ICCAD Ran Chen, Shoubo Hu, Zhitang Chen, Shengyu Zhu, Bei Yu, Pengyun Li, Cheng Chen, Yu Huang, Jianye Hao
2021	J	`jnl`	Asymptotically Optimal One- and Two-Sample Testing With Kernels. IEEE Trans. Inf. Theory Shengyu Zhu, Biao Chen, Zhitang Chen, Pengfei Yang
2021	A*	`conf`	Ordering-Based Causal Discovery with Reinforcement Learning. IJCAI Xiaoqiang Wang, Yali Du, Shengyu Zhu, Liangjun Ke, Zhitang Chen, Jianye Hao, Jun Wang
2021	J	`jnl`	Ordering-Based Causal Discovery with Reinforcement Learning. CoRR Xiaoqiang Wang, Yali Du, Shengyu Zhu, Liangjun Ke, Zhitang Chen, Jianye Hao, Jun Wang
2021	J	`jnl`	gCastle: A Python Toolbox for Causal Discovery. CoRR Keli Zhang, Shengyu Zhu, Marcus Kalander, Ignavier Ng, Junjian Ye, Zhitang Chen, Lujia Pan
2020	A*	`conf`	Causal Discovery with Reinforcement Learning. ICLR Shengyu Zhu, Ignavier Ng, Zhitang Chen
2020	J	`jnl`	Low Rank Directed Acyclic Graphs and Causal Structure Learning. CoRR Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He
2019	J	`jnl`	A Graph Autoencoder Approach to Causal Structure Learning. CoRR Ignavier Ng, Shengyu Zhu, Zhitang Chen, Zhuangyan Fang
2019	J	`jnl`	Asymptotically Optimal One- and Two-Sample Testing with Kernels. CoRR Shengyu Zhu, Biao Chen, Zhitang Chen, Pengfei Yang
2019	J	`jnl`	Causal Discovery by Kernel Intrinsic Invariance Measure. CoRR Zhitang Chen, Shengyu Zhu, Yue Liu, Tim Tse
2019	J	`jnl`	Causal Discovery with Reinforcement Learning. CoRR Shengyu Zhu, Zhitang Chen
2019	J	`jnl`	Masked Gradient-Based Causal Structure Learning. CoRR Ignavier Ng, Zhuangyan Fang, Shengyu Zhu, Zhitang Chen
2019	A	`conf`	Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit. AISTATS Shengyu Zhu, Biao Chen, Pengfei Yang, Zhitang Chen
2018	J	`jnl`	Distributed Detection in Ad Hoc Networks Through Quantized Consensus. IEEE Trans. Inf. Theory Shengyu Zhu, Biao Chen
2018	J	`jnl`	Exponentially Consistent Kernel Two-Sample Tests. CoRR Shengyu Zhu, Biao Chen, Zhitang Chen
2018	J	`jnl`	Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit. CoRR Shengyu Zhu, Biao Chen, Pengfei Yang, Zhitang Chen
2017	J	`jnl`	Corrections to "Quantized Consensus by the ADMM: Probabilistic Versus Deterministic Quantizers". IEEE Trans. Signal Process. Shengyu Zhu, Biao Chen
2016	J	`jnl`	Distributed Detection in Ad Hoc Networks Through Quantized Consensus-Part II: Asymptotically Optimal Detection via One-Bit Communications. CoRR Shengyu Zhu, Biao Chen
2016	—	`conf`	Distributed average consensus with bounded quantization. SPAWC Shengyu Zhu, Biao Chen
2016	B	`conf`	Distributed detection over connected networks via one-bit quantizer. ISIT Shengyu Zhu, Biao Chen
2016	J	`jnl`	Quantized Consensus by the ADMM: Probabilistic Versus Deterministic Quantizers. IEEE Trans. Signal Process. Shengyu Zhu, Biao Chen
2016	Misc	`conf`	Quantized consensus ADMM for multi-agent distributed optimization. ICASSP Shengyu Zhu, Mingyi Hong, Biao Chen
2015	—	`conf`	Distributed average consensus with deterministic quantization: An ADMM approach. GlobalSIP Shengyu Zhu, Biao Chen
2015	J	`jnl`	Quantized Consensus by the ADMM: Probabilistic versus Deterministic Quantizers. CoRR Shengyu Zhu, Biao Chen
2014	J	`jnl`	Decentralized Data Reduction With Quantization Constraints. IEEE Trans. Signal Process. Ge Xu, Shengyu Zhu, Biao Chen
2013	Misc	`conf`	Are global sufficient statistics always sufficient: The impact of quantization on decentralized data reduction. ACSSC Shengyu Zhu, Ge Xu, Biao Chen
2013	—	`conf`	Data reduction in tandem fusion systems. ChinaSIP Shengyu Zhu, Biao Chen
2013	J	`jnl`	Decentralized Data Reduction with Quantization Constraints. CoRR Ge Xu, Shengyu Zhu, Biao Chen
2013	B	`conf`	Interactive distributed detection with conditionally independent observations. WCNC Shengyu Zhu, Earnest Akofor, Biao Chen