New approaches for solving permutation indeterminacy and scaling ambiguity in frequency domain separation of convolved mixtures. - Zhitang Chen; Laiwan Chan (IJCNN, 2011)

Causal Discovery for Linear Non-Gaussian Acyclic Models in the Presence of Latent Gaussian Confounders. - Zhitang Chen; Laiwan Chan (LVA/ICA, 2012)

Causal discovery with scale-mixture model for spatiotemporal variance dependencies. - Zhitang Chen; Kun Zhang 001; Laiwan Chan (NIPS, 2012)

Nonlinear Causal Discovery for High Dimensional Data: A Kernelized Trace Method. - Zhitang Chen; Kun Zhang 001; Laiwan Chan (ICDM, 2013)

Causality in Linear Nongaussian Acyclic Models in the Presence of Latent Gaussian Confounders. - Zhitang Chen; Laiwan Chan (Neural Comput., 2013)

Causal Discovery via Reproducing Kernel Hilbert Space Embeddings. - Zhitang Chen; Kun Zhang 001; Laiwan Chan; Bernhard Schölkopf (Neural Comput., 2014)

Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings. - Zhitang Chen; Pascal Poupart; Yanhui Geng (AISTATS, 2016)

Predicting future traffic using Hidden Markov Models. - Zhitang Chen; Jiayao Wen; Yanhui Geng (ICNP, 2016)

Online flow size prediction for improved network routing. - Pascal Poupart; Zhitang Chen; Priyank Jaini; Fred Fung; Hengky Susanto; Yanhui Geng; Li Chen 008; Kai Chen 005; Hao Jin (ICNP, 2016)

Online Algorithms for Sum-Product Networks with Continuous Variables. - Priyank Jaini; Abdullah Rashwan; Han Zhao 002; Yue Liu; Ershad Banijamali; Zhitang Chen; Pascal Poupart (Probabilistic Graphical Models, 2016)

Seq2Img: A sequence-to-image based approach towards IP traffic classification using convolutional neural networks. - Zhitang Chen; Ke He; Jian Li; Yanhui Geng (IEEE BigData, 2017)

Cellular network configuration via online learning and joint optimization. - Xueying Guo; George Trimponias; Xiaoxiao Wang 002; Zhitang Chen; Yanhui Geng; Xin Liu 002 (IEEE BigData, 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 (ICLR (Poster), 2017)

Faster Policy Adaptation in Environments with Exogeneity: A State Augmentation Approach. - Zhuoshu Li; Zhitang Chen; Pascal Poupart; Sanmay Das; Yanhui Geng (AAMAS, 2018)

A Hybrid Brain Computer Interface Driven by Motor Imagery of Right Hand Versus Right Forearm. - Zhitang Chen; Xin Zhao 006; Zhongpeng Wang; Kun Wang 053; Weibo Yi; Feng He 005; Hongzhi Qi (iCAST, 2018)

Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning. - Thomas G. Dietterich; George Trimponias; Zhitang Chen (ICML, 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 (NeurIPS, 2018)

Discriminative Training of Sum-Product Networks by Extended Baum-Welch. - Abdullah Rashwan; Pascal Poupart; Zhitang Chen (PGM, 2018)

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

Learning-Based Joint Configuration for Cellular Networks. - Xueying Guo; George Trimponias; Xiaoxiao Wang 002; Zhitang Chen; Yanhui Geng; Xin Liu 002 (IEEE Internet Things J., 2018)

A Kernel Embedding-Based Approach for Nonstationary Causal Model Inference. - Shoubo Hu; Zhitang Chen; Laiwan Chan (Neural Comput., 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)

Kernel-based Multi-Task Contextual Bandits in Cellular Network Configuration. - Xiaoxiao Wang 002; Xueying Guo; Jie Chuai; Zhitang Chen; Xin Liu 002 (IEEE BigData, 2019)

A Collaborative Learning Based Approach for Parameter Configuration of Cellular Networks. - Jie Chuai; Zhitang Chen; Guochen Liu; Xueying Guo; Xiaoxiao Wang 002; Xin Liu 002; Chongming Zhu; Feiyi Shen (INFOCOM, 2019)

Domain Generalization via Multidomain Discriminant Analysis. - Shoubo Hu; Kun Zhang 001; Zhitang Chen; Laiwan Chan (UAI, 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 053; Weibo Yi; Hongzhi Qi (IEEE Access, 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)

Model-free inference of diffusion networks using RKHS embeddings. - Shoubo Hu; Bogdan Cautis; Zhitang Chen; Laiwan Chan; Yanhui Geng; Xiuqiang He 001 (Data Min. Knowl. Discov., 2019)

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

Stable Learning via Differentiated Variable Decorrelation. - Zheyan Shen; Peng Cui 001; Jiashuo Liu; Tong Zhang 001; Bo Li 064; Zhitang Chen (KDD, 2020)

CausalVAE: Structured Causal Disentanglement in Variational Autoencoder. - Mengyue Yang; Furui Liu; Zhitang Chen; Xinwei Shen 002; Jianye Hao; Jun Wang 012 (CoRR, 2020)

Clustering Causal Additive Noise Models. - Vahid Partovi Nia; Xinlin Li; Masoud Asgharian; Shoubo Hu; Zhitang Chen; Yanhui Geng (CoRR, 2020)

Decoder-free Robustness Disentanglement without (Additional) Supervision. - Yifei Wang 001; Dan Peng; Furui Liu; Zhenguo Li; Zhitang Chen; Jiansheng Yang (CoRR, 2020)

Disentangled Generative Causal Representation Learning. - Xinwei Shen 002; Furui Liu; Hanze Dong; Qing Lian; Zhitang Chen; Tong Zhang 001 (CoRR, 2020)

Causal World Models by Unsupervised Deconfounding of Physical Dynamics. - Minne Li; Mengyue Yang; Furui Liu; Xu Chen 017; Zhitang Chen; Jun Wang 012 (CoRR, 2020)

Discriminative training of feed-forward and recurrent sum-product networks by extended Baum-Welch. - Haonan Duan 002; Abdullah Rashwan; Pascal Poupart; Zhitang Chen (Int. J. Approx. Reason., 2020)

CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models. - Mengyue Yang; Furui Liu; Zhitang Chen; Xinwei Shen 002; Jianye Hao; Jun Wang 012 (CVPR, 2021)

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 (ICCAD, 2021)

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)

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)

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 012; Jan Peters 001; Haitham Bou-Ammar (CoRR, 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)

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)

Learning to Construct Nested Polar Codes: An Attention-Based Set-to-Element Model. - Yang Li 035; Zhitang Chen; Guochen Liu; Yik-Chung Wu; Kai-Kit Wong (IEEE Commun. Lett., 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)

DREAMPlace 4.0: Timing-driven Global Placement with Momentum-based Net Weighting. - Peiyu Liao; Siting Liu 002; Zhitang Chen; Wenlong Lv; Yibo Lin; Bei Yu 001 (DATE, 2022)

FastGR: Global Routing on CPU-GPU with Heterogeneous Task Graph Scheduler. - Siting Liu 002; Peiyu Liao; Rui Zhang; Zhitang Chen; Wenlong Lv; Yibo Lin; Bei Yu 001 (DATE, 2022)

Batch Sequential Black-Box Optimization with Embedding Alignment Cells for Logic Synthesis. - Chang Feng; Wenlong Lyu; Zhitang Chen; Junjie Ye 002; Mingxuan Yuan; Jianye Hao (ICCAD, 2022)

GraphHO: A Graph-based Handover Optimization System for Cellular Networks. - Lin Yang; Min Cheng; Jun Qu; Zhitang Chen (ISWCS, 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)

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)

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)

Generalizable Information Theoretic Causal Representation. - Mengyue Yang; Xinyu Cai; Furui Liu; Xu Chen 017; Zhitang Chen; Jianye Hao; Jun Wang 012 (CoRR, 2022)

Weakly Supervised Disentangled Generative Causal Representation Learning. - Xinwei Shen 002; Furui Liu; Hanze Dong; Qing Lian; Zhitang Chen; Tong Zhang 001 (J. Mach. Learn. Res., 2022)

Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network. - Mehrtash Mehrabi; Walid Masoudimansour; Yingxue Zhang 001; Jie Chuai; Zhitang Chen; Mark Coates; Jianye Hao; Yanhui Geng (AAAI, 2023)

A Novel Extrapolation Technique to Accelerate WMMSE. - Kaiwen Zhou 001; Zhilin Chen; Guochen Liu; Zhitang Chen (ICASSP, 2023)

FastGR: Global Routing on CPU-GPU with Heterogeneous Task Graph Scheduler (Extended Abstract). - Siting Liu 002; Yuan Pu 001; Peiyu Liao; Hongzhong Wu; Rui Zhang; Zhitang Chen; Wenlong Lv; Yibo Lin; Bei Yu 001 (IJCAI, 2023)

Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs. - Lin Yang; Junlong Lyu; Wenlong Lyu; Zhitang Chen (NeurIPS, 2023)

Reweighted Interacting Langevin Diffusions: an Accelerated Sampling Methodfor Optimization. - Junlong Lyu; Zhitang Chen; Wenlong Lyu; Jianye Hao (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)

Convergence guarantee for consistency models. - Junlong Lyu; Zhitang Chen; Shoubo Feng (CoRR, 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)

FastGR: Global Routing on CPU-GPU With Heterogeneous Task Graph Scheduler. - Siting Liu 002; Yuan Pu 001; Peiyu Liao; Hongzhong Wu; Rui Zhang; Zhitang Chen; Wenlong Lv; Yibo Lin; Bei Yu 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

Sampling is as easy as keeping the consistency: convergence guarantee for Consistency Models. - Junlong Lyu; Zhitang Chen; Shoubo Feng (ICML, 2024)

Causal Coordinated Concurrent Reinforcement Learning. - Tim Tse; Isaac Chan; Zhitang Chen (CoRR, 2024)

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)

Cooperative Multi-Model Training for Personalized Federated Learning Over Heterogeneous Devices. - Jian Xu 016; Shuo Wan; Yinchuan Li; Sichun Luo; Zhilin Chen; Yunfeng Shao 001; Zhitang Chen; Shao-Lun Huang; Linqi Song (IEEE J. Sel. Top. Signal Process., 2025)

Boosting Generalization in Diffusion-Based Neural Combinatorial Solver via Energy-guided Sampling. - Haoyu Lei; Kaiwen Zhou; Yinchuan Li; Zhitang Chen; Farzan Farnia (CoRR, 2025)

Generative Models in Decision Making: A Survey. - Yinchuan Li; Xinyu Shao; Jianping Zhang; Haozhi Wang; Leo Maxime Brunswic; Kaiwen Zhou; Jiqian Dong; Kaiyang Guo; Xiu Li 001; Zhitang Chen; Jun Wang 012; Jianye Hao (CoRR, 2025)

Proximalized Preference Optimization for Diverse Feedback Types: A Decomposed Perspective on DPO. - Kaiyang Guo; Yinchuan Li; Zhitang Chen (CoRR, 2025)

Learning Design-Score Manifold to Guide Diffusion Models for Offline Optimization. - Tailin Zhou; Zhilin Chen; Wenlong Lyu; Zhitang Chen; Danny H. K. Tsang; Jun Zhang 004 (CoRR, 2025)