A Theoretical Framework of the Graph Shift Algorithm. - Xuhui Fan 001; Longbing Cao (AAAI, 2012)

Maximum margin clustering on evolutionary data. - Xuhui Fan 001; Lin Zhu; Longbing Cao; Xia Cui 002; Yew-Soon Ong (CIKM, 2012)

Model the complex dependence structures of financial variables by using canonical vine. - Wei Wei 039; Xuhui Fan 001; Jinyan Li 001; Longbing Cao (CIKM, 2012)

Copula Mixed-Membership Stochastic Blockmodel for Intra-Subgroup Correlations. - Xuhui Fan 001; Longbing Cao; Richard Yi Da Xu (CoRR, 2013)

Learning Hidden Structures with Relational Models by Adequately Involving Rich Information in A Network. - Xuhui Fan 001; Richard Yi Da Xu; Longbing Cao; Yin Song (CoRR, 2013)

Non-parametric Power-law Data Clustering. - Xuhui Fan 001; Yiling Zeng; Longbing Cao (CoRR, 2013)

Characterizing A Database of Sequential Behaviors with Latent Dirichlet Hidden Markov Models - Yin Song; Longbing Cao; Xuhui Fan 001; Wei Cao 012; Jian Zhang 002 (CoRR, 2013)

A convergence theorem for graph shift-type algorithms. - Xuhui Fan 001; Longbing Cao (Pattern Recognit., 2015)

Dynamic Infinite Mixed-Membership Stochastic Blockmodel. - Xuhui Fan 001; Longbing Cao; Richard Yi Da Xu (IEEE Trans. Neural Networks Learn. Syst., 2015)

Nonparametric Bayesian models for learning network coupling relationships - Xuhui Fan 001 (2015)

The Ostomachion Process. - Xuhui Fan 001; Bin Li 015; Yi Wang 041; Yang Wang 002; Fang Chen 001 (AAAI, 2016)

Copula Mixed-Membership Stochastic Blockmodel. - Xuhui Fan 001; Richard Yi Da Xu; Longbing Cao (IJCAI, 2016)

Bayesian Optimization of Partition Layouts for Mondrian Processes. - Yi Wang 041; Bin Li 015; Xuhui Fan 001; Yang Wang 002; Fang Chen 001 (IJCAI, 2016)

Stochastic Patching Process. - Xuhui Fan 001; Bin Li 015; Yi Wang 041; Yang Wang 002; Fang Chen 001 (CoRR, 2016)

Learning Nonparametric Relational Models by Conjugately Incorporating Node Information in a Network. - Xuhui Fan 001; Richard Yi Da Xu; Longbing Cao; Yin Song (IEEE Trans. Cybern., 2017)

The Binary Space Partitioning-Tree Process. - Xuhui Fan 001; Bin Li 015; Scott A. Sisson (AISTATS, 2018)

Rectangular Bounding Process. - Xuhui Fan 001; Bin Li 015; Scott A. Sisson (NeurIPS, 2018)

Corrosion Prediction on Sewer Networks with Sparse Monitoring Sites: A Case Study. - Jianjia Zhang; Bin Li 015; Xuhui Fan 001; Yang Wang 002; Fang Chen 001 (PAKDD (1), 2018)

A Refined MISD Algorithm Based on Gaussian Process Regression. - Feng Zhou 011; Zhidong Li; Xuhui Fan 001; Yang Wang 002; Arcot Sowmya; Fang Chen 001 (PAKDD (2), 2018)

Binary Space Partitioning Forest. - Xuhui Fan 001; Bin Li 015; Scott A. Sisson (AISTATS, 2019)

Scalable Deep Generative Relational Model with High-Order Node Dependence. - Xuhui Fan 001; Bin Li 015; Caoyuan Li; Scott A. Sisson; Ling Chen 006 (NeurIPS, 2019)

Hawkes Process with Stochastic Triggering Kernel. - Feng Zhou 011; Yixuan Zhang 006; Zhidong Li; Xuhui Fan 001; Yang Wang 002; Arcot Sowmya; Fang Chen 001 (PAKDD (1), 2019)

Binary Space Partitioning Forests. - Xuhui Fan 001; Bin Li 015; Scott Anthony Sisson (CoRR, 2019)

Scalable Inference for Nonparametric Hawkes Process Using Pólya-Gamma Augmentation. - Feng Zhou 011; Zhidong Li; Xuhui Fan 001; Yang Wang 002; Arcot Sowmya; Fang Chen 001 (CoRR, 2019)

Scalable Deep Generative Relational Models with High-Order Node Dependence. - Xuhui Fan 001; Bin Li 015; Scott Anthony Sisson; Caoyuan Li; Ling Chen 006 (CoRR, 2019)

Image Denoising Based on Nonlocal Bayesian Singular Value Thresholding and Stein's Unbiased Risk Estimator. - Caoyuan Li; Hong-Bo Xie; Xuhui Fan 001; Richard Yi Da Xu; Sabine Van Huffel; Scott A. Sisson; Kerrie L. Mengersen (IEEE Trans. Image Process., 2019)

Fragmentation Coagulation Based Mixed Membership Stochastic Blockmodel. - Zheng Yu; Xuhui Fan 001; Marcin Pietrasik; Marek Z. Reformat (AAAI, 2020)

Online Binary Space Partitioning Forests. - Xuhui Fan 001; Bin Li 015; Scott A. Sisson (AISTATS, 2020)

Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling. - Yaqiong Li; Xuhui Fan 001; Ling Chen 006; Bin Li 015; Zheng Yu; Scott A. Sisson (IJCAI, 2020)

Recurrent Dirichlet Belief Networks for Interpretable Dynamic Relational Data Modelling. - Yaqiong Li; Xuhui Fan 001; Ling Chen 006; Bin Li 015; Scott A. Sisson (CoRR, 2020)

Supervised Categorical Metric Learning with Schatten p-Norms. - Xuhui Fan 001; Éric Gaussier (CoRR, 2020)

Fast multi-resolution segmentation for nonstationary Hawkes process using cumulants. - Feng Zhou 011; Zhidong Li; Xuhui Fan 001; Yang Wang 002; Arcot Sowmya; Fang Chen 001 (Int. J. Data Sci. Anal., 2020)

Bayesian Nonnegative Matrix Factorization With Dirichlet Process Mixtures. - Caoyuan Li; Hong-Bo Xie; Kerrie L. Mengersen; Xuhui Fan 001; Richard Yi Da Xu; Scott A. Sisson; Sabine Van Huffel (IEEE Trans. Signal Process., 2020)

Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks. - Xuhui Fan 001; Bin Li 015; Yaqiong Li; Scott A. Sisson (ICML, 2021)

Bayesian Nonparametric Space Partitions: A Survey. - Xuhui Fan 001; Bin Li 015; Ling Luo 002; Scott A. Sisson (IJCAI, 2021)

Continuous-time edge modelling using non-parametric point processes. - Xuhui Fan 001; Bin Li 015; Feng Zhou 011; Scott A. Sisson (NeurIPS, 2021)

Decoupling Sparsity and Smoothness in Dirichlet Belief Networks. - Yaqiong Li; Xuhui Fan 001; Ling Chen 006; Bin Li 015; Scott A. Sisson (ECML/PKDD (2), 2021)

Efficient EM-variational inference for nonparametric Hawkes process. - Feng Zhou 011; Simon Luo; Zhidong Li; Xuhui Fan 001; Yang Wang 002; Arcot Sowmya; Fang Chen 001 (Stat. Comput., 2021)

Kernelized Sparse Bayesian Matrix Factorization. - Caoyuan Li; Hong-Bo Xie; Xuhui Fan 001; Richard Yi Da Xu; Sabine Van Huffel; Kerrie L. Mengersen (IEEE Trans. Neural Networks Learn. Syst., 2021)

Smoothing graphons for modelling exchangeable relational data. - Yaqiong Li; Xuhui Fan 001; Ling Chen 006; Bin Li 015; Scott A. Sisson (Mach. Learn., 2022)

Supervised Categorical Metric Learning With Schatten p-Norms. - Yaqiong Li; Xuhui Fan 001; Éric Gaussier (IEEE Trans. Cybern., 2022)

Free-Form Variational Inference for Gaussian Process State-Space Models. - Xuhui Fan 001; Edwin V. Bonilla; Terence J. O'Kane; Scott A. Sisson (ICML, 2023)

Bayesian Federated Learning: A Survey. - Longbing Cao; Hui Chen 026; Xuhui Fan 001; João Gama 001; Yew-Soon Ong; Vipin Kumar 001 (CoRR, 2023)

Hawkes Processes With Stochastic Exogenous Effects for Continuous-Time Interaction Modelling. - Xuhui Fan 001; Yaqiong Li; Ling Chen 006; Bin Li 015; Scott A. Sisson (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Dynamic customer segmentation via hierarchical fragmentation-coagulation processes. - Ling Luo 002; Bin Li 015; Xuhui Fan 001; Yang Wang 002; Irena Koprinska; Fang Chen 001 (Mach. Learn., 2023)

TransFeat-TPP: An Interpretable Deep Covariate Temporal Point Processes. - Zizhuo Meng; Boyu Li 003; Xuhui Fan 001; Zhidong Li; Yang Wang 002; Fang Chen 001; Feng Zhou 011 (ECAI, 2024)

Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation. - Yididiya Y. Nadew; Xuhui Fan 001; Christopher John Quinn (ICML, 2024)

Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data. - Zhilin Zhao 001; Longbing Cao; Xuhui Fan 001; Wei-Shi Zheng 001 (NeurIPS, 2024)

Nonstationary Sparse Spectral Permanental Process. - Zicheng Sun; Yixuan Zhang 006; Zenan Ling; Xuhui Fan 001; Feng Zhou 011 (NeurIPS, 2024)

FedSI: Federated Subnetwork Inference for Efficient Uncertainty Quantification. - Hui Chen 026; Hengyu Liu 001; Zhangkai Wu; Xuhui Fan 001; Longbing Cao (CoRR, 2024)

ParamReL: Learning Parameter Space Representation via Progressively Encoding Bayesian Flow Networks. - Zhangkai Wu; Xuhui Fan 001; Jin Li 002; Zhilin Zhao 001; Hui Chen 026; Longbing Cao (CoRR, 2024)

Federated Neural Nonparametric Point Processes. - Hui Chen 026; Hengyu Liu 001; Yaqiong Li; Xuhui Fan 001; Zhilin Zhao 001; Feng Zhou 011; Christopher John Quinn; Longbing Cao (CoRR, 2024)

Learning Coupled Subspaces for Multi-Condition Spike Data. - Yididiya Y. Nadew; Xuhui Fan 001; Christopher J. Quinn (CoRR, 2024)

Marked Temporal Bayesian Flow Point Processes. - Hui Chen 026; Xuhui Fan 001; Hengyu Liu 001; Longbing Cao (CoRR, 2024)

Navigating Towards Fairness with Data Selection. - Yixuan Zhang 006; Zhidong Li; Yang Wang 002; Fang Chen 001; Xuhui Fan 001; Feng Zhou 011 (AAAI, 2025)

Dynamic Spectral Graph Anomaly Detection. - Jianbo Zheng; Chao Yang 015; Tairui Zhang; Longbing Cao; Bin Jiang 006; Xuhui Fan 001; Xiao-Ming Wu 002; Xianxun Zhu (AAAI, 2025)

ProgDiffusion: Progressively Self-encoding Diffusion Models. - Zhangkai Wu; Xuhui Fan 001; Longbing Cao (KDD (1), 2025)

A client-server based recognition system: Non-contact single/multiple emotional and behavioral state assessment methods. - Xianxun Zhu; Zhaozhao Liu; Erik Cambria; Xiaohan Yu 001; Xuhui Fan 001; Hui Chen 026; Rui Wang 034 (Comput. Methods Programs Biomed., 2025)

A Survey on Pre-Trained Diffusion Model Distillations. - Xuhui Fan 001; Zhangkai Wu; Hongyu Wu (CoRR, 2025)

TraFlow: Trajectory Distillation on Pre-Trained Rectified Flow. - Zhangkai Wu; Xuhui Fan 001; Hongyu Wu; Longbing Cao (CoRR, 2025)

FigBO: A Generalized Acquisition Function Framework with Look-Ahead Capability for Bayesian Optimization. - Hui Chen 026; Xuhui Fan 001; Zhangkai Wu; Longbing Cao (CoRR, 2025)

Contrastive-Based Removal of Negative Information in Multimodal Emotion Analysis. - Rui Wang 034; Yaoyang Wang; Erik Cambria; Xuhui Fan 001; Xiaohan Yu 001; Yao Huang; Xiaosong E; Xianxun Zhu (Cogn. Comput., 2025)