Zhitang Chen

According to our database, Zhitang Chen authored at least 72 papers between 2011 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

Causal Coordinated Concurrent Reinforcement Learning.

Tim Tse, Isaac Chan, Zhitang Chen

CoRR, 2024

2023

FastGR: Global Routing on CPU-GPU With Heterogeneous Task Graph Scheduler.

Siting Liu, Yuan Pu, Peiyu Liao, Hongzhong Wu, Rui Zhang, Zhitang Chen, Wenlong Lv, Yibo Lin, Bei Yu

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

Contrastive-ACE: Domain Generalization Through Alignment of Causal Mechanisms.

Yunqi Wang, Furui Liu, Zhitang Chen, Yik-Chung Wu, Jianye Hao, Guangyong Chen, Pheng-Ann Heng

IEEE Trans. Image Process., 2023

Convergence guarantee for consistency models.

Junlong Lyu, Zhitang Chen, Shoubo Feng

CoRR, 2023

Efficient Bayesian Optimization with Deep Kernel Learning and Transformer Pre-trained on Multiple Heterogeneous Datasets.

Wenlong Lyu, Shoubo Hu, Jie Chuai, Zhitang Chen

CoRR, 2023

Reweighted Interacting Langevin Diffusions: an Accelerated Sampling Methodfor Optimization.

Junlong Lyu, Zhitang Chen, Wenlong Lyu, Jianye Hao

CoRR, 2023

Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs.

Lin Yang, Junlong Lyu, Wenlong Lyu, Zhitang Chen

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

FastGR: Global Routing on CPU-GPU with Heterogeneous Task Graph Scheduler (Extended Abstract).

Siting Liu, Yuan Pu, Peiyu Liao, Hongzhong Wu, Rui Zhang, Zhitang Chen, Wenlong Lv, Yibo Lin, Bei Yu

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

A Novel Extrapolation Technique to Accelerate WMMSE.

Kaiwen Zhou, Zhilin Chen, Guochen Liu, Zhitang Chen

Proceedings of the IEEE International Conference on Acoustics, 2023

Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network.

Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang, Jie Chuai, Zhitang Chen, Mark Coates, Jianye Hao, Yanhui Geng

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Weakly Supervised Disentangled Generative Causal Representation Learning.

Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang

J. Mach. Learn. Res., 2022

Generalizable Information Theoretic Causal Representation.

Mengyue Yang, Xinyu Cai, Furui Liu, Xu Chen, Zhitang Chen, Jianye Hao, Jun Wang

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

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

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

GraphHO: A Graph-based Handover Optimization System for Cellular Networks.

Lin Yang, Min Cheng, Jun Qu, Zhitang Chen

Proceedings of the 18th International Symposium on Wireless Communication Systems, 2022

Batch Sequential Black-Box Optimization with Embedding Alignment Cells for Logic Synthesis.

Chang Feng, Wenlong Lyu, Zhitang Chen, Junjie Ye, Mingxuan Yuan, Jianye Hao

Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, 2022

FastGR: Global Routing on CPU-GPU with Heterogeneous Task Graph Scheduler.

Siting Liu, Peiyu Liao, Rui Zhang, Zhitang Chen, Wenlong Lv, Yibo Lin, Bei Yu

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

DREAMPlace 4.0: Timing-driven Global Placement with Momentum-based Net Weighting.

Peiyu Liao, Siting Liu, Zhitang Chen, Wenlong Lv, Yibo Lin, Bei Yu

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 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

Learning to Construct Nested Polar Codes: An Attention-Based Set-to-Element Model.

Yang Li, Zhitang Chen, Guochen Liu, Yik-Chung Wu, Kai-Kit Wong

IEEE Commun. Lett., 2021

Physics Constrained Flow Neural Network for Short-Timescale Predictions in Data Communications Networks.

Xiangle Cheng, James He, Shihan Xiao, Yingxue Zhang, Zhitang Chen, Pascal Poupart, Fenglin Li

CoRR, 2021

gCastle: A Python Toolbox for Causal Discovery.

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

CoRR, 2021

High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning.

Antoine Grosnit, Rasul Tutunov, Alexandre Max Maraval, Ryan-Rhys Griffiths, Alexander I. Cowen-Rivers, Lin Yang, Lin Zhu, Wenlong Lyu, Zhitang Chen, Jun Wang, Jan Peters, Haitham Bou-Ammar

CoRR, 2021

Contrastive ACE: Domain Generalization Through Alignment of Causal Mechanisms.

Yunqi Wang, Furui Liu, Zhitang Chen, Qing Lian, Shoubo Hu, Jianye Hao, Yik-Chung Wu

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

CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models.

Mengyue Yang, Furui Liu, Zhitang Chen, Xinwei Shen, Jianye Hao, Jun Wang

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Discriminative training of feed-forward and recurrent sum-product networks by extended Baum-Welch.

Haonan Duan, Abdullah Rashwan, Pascal Poupart, Zhitang Chen

Int. J. Approx. Reason., 2020

Causal World Models by Unsupervised Deconfounding of Physical Dynamics.

Minne Li, Mengyue Yang, Furui Liu, Xu Chen, Zhitang Chen, Jun Wang

CoRR, 2020

Disentangled Generative Causal Representation Learning.

Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang

CoRR, 2020

Decoder-free Robustness Disentanglement without (Additional) Supervision.

Yifei Wang, Dan Peng, Furui Liu, Zhenguo Li, Zhitang Chen, Jiansheng Yang

CoRR, 2020

Clustering Causal Additive Noise Models.

Vahid Partovi Nia, Xinlin Li, Masoud Asgharian, Shoubo Hu, Zhitang Chen, Yanhui Geng

CoRR, 2020

CausalVAE: Structured Causal Disentanglement in Variational Autoencoder.

Mengyue Yang, Furui Liu, Zhitang Chen, Xinwei Shen, Jianye Hao, Jun Wang

CoRR, 2020

Stable Learning via Differentiated Variable Decorrelation.

Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang, Bo Li, Zhitang Chen

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Causal Discovery with Reinforcement Learning.

Shengyu Zhu, Ignavier Ng, Zhitang Chen

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

2019

Model-free inference of diffusion networks using RKHS embeddings.

Shoubo Hu, Bogdan Cautis, Zhitang Chen, Laiwan Chan, Yanhui Geng, Xiuqiang He

Data Min. Knowl. Discov., 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

Recognizing Motor Imagery Between Hand and Forearm in the Same Limb in a Hybrid Brain Computer Interface Paradigm: An Online Study.

Zhitang Chen, Zhongpeng Wang, Kun Wang, Weibo Yi, Hongzhi Qi

IEEE Access, 2019

Domain Generalization via Multidomain Discriminant Analysis.

Shoubo Hu, Kun Zhang, Zhitang Chen, Laiwan Chan

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

A Collaborative Learning Based Approach for Parameter Configuration of Cellular Networks.

Jie Chuai, Zhitang Chen, Guochen Liu, Xueying Guo, Xiaoxiao Wang, Xin Liu, Chongming Zhu, Feiyi Shen

Proceedings of the 2019 IEEE Conference on Computer Communications, 2019

Kernel-based Multi-Task Contextual Bandits in Cellular Network Configuration.

Xiaoxiao Wang, Xueying Guo, Jie Chuai, Zhitang Chen, Xin Liu

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 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

A Kernel Embedding-Based Approach for Nonstationary Causal Model Inference.

Shoubo Hu, Zhitang Chen, Laiwan Chan

Neural Comput., 2018

Learning-Based Joint Configuration for Cellular Networks.

Xueying Guo, George Trimponias, Xiaoxiao Wang, Zhitang Chen, Yanhui Geng, Xin Liu

IEEE Internet Things J., 2018

Exponentially Consistent Kernel Two-Sample Tests.

Shengyu Zhu, Biao Chen, Zhitang Chen

CoRR, 2018

Discriminative Training of Sum-Product Networks by Extended Baum-Welch.

Abdullah Rashwan, Pascal Poupart, Zhitang Chen

Proceedings of the International Conference on Probabilistic Graphical Models, 2018

Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models.

Shoubo Hu, Zhitang Chen, Vahid Partovi Nia, Lai-Wan Chan, Yanhui Geng

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning.

Thomas G. Dietterich, George Trimponias, Zhitang Chen

Proceedings of the 35th International Conference on Machine Learning, 2018

A Hybrid Brain Computer Interface Driven by Motor Imagery of Right Hand Versus Right Forearm.

Zhitang Chen, Xin Zhao, Zhongpeng Wang, Kun Wang, Weibo Yi, Feng He, Hongzhi Qi

Proceedings of the 9th International Conference on Awareness Science and Technology, 2018

Faster Policy Adaptation in Environments with Exogeneity: A State Augmentation Approach.

Zhuoshu Li, Zhitang Chen, Pascal Poupart, Sanmay Das, Yanhui Geng

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017

Online Bayesian Transfer Learning for Sequential Data Modeling.

Priyank Jaini, Zhitang Chen, Pablo Carbajal, Edith Law, Laura Middleton, Kayla Regan, Mike Schaekermann, George Trimponias, James Tung, Pascal Poupart

Proceedings of the 5th International Conference on Learning Representations, 2017

Cellular network configuration via online learning and joint optimization.

Xueying Guo, George Trimponias, Xiaoxiao Wang, Zhitang Chen, Yanhui Geng, Xin Liu

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

Seq2Img: A sequence-to-image based approach towards IP traffic classification using convolutional neural networks.

Zhitang Chen, Ke He, Jian Li, Yanhui Geng

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016

Online Algorithms for Sum-Product Networks with Continuous Variables.

Priyank Jaini, Abdullah Rashwan, Han Zhao, Yue Liu, Ershad Banijamali, Zhitang Chen, Pascal Poupart

Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

Online flow size prediction for improved network routing.

Pascal Poupart, Zhitang Chen, Priyank Jaini, Fred Fung, Hengky Susanto, Yanhui Geng, Li Chen, Kai Chen, Hao Jin

Proceedings of the 24th IEEE International Conference on Network Protocols, 2016

Predicting future traffic using Hidden Markov Models.

Zhitang Chen, Jiayao Wen, Yanhui Geng

Proceedings of the 24th IEEE International Conference on Network Protocols, 2016

Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings.

Zhitang Chen, Pascal Poupart, Yanhui Geng

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2014

Causal Discovery via Reproducing Kernel Hilbert Space Embeddings.

Zhitang Chen, Kun Zhang, Laiwan Chan, Bernhard Schölkopf

Neural Comput., 2014

2013

Causality in Linear Nongaussian Acyclic Models in the Presence of Latent Gaussian Confounders.

Zhitang Chen, Laiwan Chan

Neural Comput., 2013

Nonlinear Causal Discovery for High Dimensional Data: A Kernelized Trace Method.

Zhitang Chen, Kun Zhang, Laiwan Chan

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012

Causal discovery with scale-mixture model for spatiotemporal variance dependencies.

Zhitang Chen, Kun Zhang, Laiwan Chan

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Causal Discovery for Linear Non-Gaussian Acyclic Models in the Presence of Latent Gaussian Confounders.

Zhitang Chen, Laiwan Chan

Proceedings of the Latent Variable Analysis and Signal Separation, 2012

2011

New approaches for solving permutation indeterminacy and scaling ambiguity in frequency domain separation of convolved mixtures.

Zhitang Chen, Laiwan Chan

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011