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  1. H. Cao, Z. Meng, T. Ke, F. Zhou*, "Is Score Matching Suitable for Estimating Point Processes?", NeurIPS 2024. [pdf][code]

  2. Z. Sun, Y. Zhang, Z. Ling, X. Fan, F. Zhou*, "Nonstationary Sparse Spectral Permanental Process", NeurIPS 2024. [pdf][code]

  3. Z. Zhang, X. Lu, F. Zhou*, "Conjugate Bayesian Two-step Change Point Detection for Hawkes Process", NeurIPS 2024. [pdf][code]

  4. Z. Deng, F. Zhou, J. Chen, G. Wu, J. Zhu, "Calibrating Deep Ensemble through Functional Variational Inference", Transactions on Machine Learning Research.

  5. Z. Meng, B. Li, X. Fan, Z. Li, Y. Wang, F. Chen, F. Zhou*, "TransFeat-TPP: An Interpretable Deep Covariate Temporal Point Processes", ECAI 2024. [pdf][code]

  6. Z. Meng, K. Wan, Y. Huang, Z. Li, Y. Wang, F. Zhou*, "Interpretable Transformer Hawkes Processes: Unveiling Complex Interactions in Social Networks", KDD 2024. [pdf][code]

  7. T. Ke, H. Cao, F. Zhou*, "Accelerating Convergence in Bayesian Few-Shot Classification", ICML 2024. [pdf][code]

  8. Z. Ling, L. Li, Z. Feng, Y. Zhang, F. Zhou, R. Qiu, Z. Liao, "Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures", ICML 2024. [pdf]

  9. X. Fan, Z. Wu, H. Chen, F. Zhou, C. Quinn, L. Cao, "Deep Variational Learning", Tutorial IJCAI 2024.

  10. Y. Miao, Y. Lei, F. Zhou*, Z. Deng*, "Bayesian Exploration of Pre-trained Models for Low-shot Image Classification", CVPR 2024. [pdf]

  11. Y. Zhang, B. Li, Z. Ling, F. Zhou*, "Mitigating Label Bias in Machine Learning: Fairness through Confident Learning", AAAI 2024. [pdf][code]

  12. T. Ke, H. Cao, Z. Ling, F. Zhou*, "Revisiting Logistic-softmax Likelihood in Bayesian Meta-learning for Few-shot Classification", NeurIPS 2023. [pdf][code]

  13. Y. Zhang, Q. Kong, F. Zhou*, "Integration-free Training for Spatio-temporal Multimodal Covariate Deep Kernel Point Processes", NeurIPS 2023. [pdf]

  14. F. Zhou, Q. Kong, Z. Deng, F. He, P. Cui, J. Zhu*, "Heterogeneous Multi-task Gaussian Cox Processes", Machine Learning. [pdf][code]

  15. Y. Mou, J. Geng, F. Zhou*, O. Beyan, C. Rong, S. Decker, "pFedV: Mitigating Feature Distribution Skewness via Personalized Federated Learning with Variational Distribution Constraints", PAKDD 2023. [pdf][code]

  16. Y. Zhang, F. Zhou*, Z. Li, Y. Wang, F. Chen, "Fair Representation Learning with Unreliable Labels", AISTATS 2023. [pdf][code]

  17. Z. Deng, F. Zhou, J. Zhu*, "Accelerated Linearized Laplace Approximation for Bayesian Deep Learning", NeurIPS 2022. [pdf][code]

  18. F. Zhou, Q. Kong, Z. Deng, J. Kan, Y. Zhang, C. Feng, J. Zhu*, "Efficient Inference for Dynamic Flexible Interactions of Neural Populations", Journal of Machine Learning Research. [pdf][code]

  19. X. Fan, B. Li, F. Zhou, S. Sisson, "Continuous-Time Edge Modelling Using Non-Parametric Point Processes", NeurIPS 2021. [pdf][code]

  20. Y. Zhang, F. Zhou, Z. Li, Y. Wang, F. Chen, "Bias-Tolerant Fair Classification", ACML 2021. [pdf]

  21. F. Zhou, S. Luo, Z. Li*, X. Fan, Y. Wang, A. Sowmya, F. Chen, "Efficient EM-Variational Inference for Nonparametric Hawkes Process", Statistics and Computing. [pdf][code]

  22. F. Zhou, Y. Zhang, J. Zhu*, "Efficient Inference of Flexible Interaction in Spiking-neuron Networks", ICLR 2021. [pdf][code]

  23. F. Zhou, Z. Li, X. Fan, Y. Wang, A. Sowmya, F. Chen, "Efficient Inference for Nonparametric Hawkes Processes Using Auxiliary Latent Variables", Journal of Machine Learning Research. [pdf][code]

  24. S. Luo, F. Zhou, L. Azizi, M. Sugiyama, "Learning Joint Intensity in a Multivariate Poisson Process on Statistical Manifolds", NeurIPS 2020. [pdf]

  25. F. Zhou*, Z. Li, X. Fan, Y. Wang, A. Sowmya, F. Chen, "Fast Multi-resolution Segmentation for Nonstationary Hawkes Process Using Cumulants", International Journal of Data Science and Analytics. [pdf]

  26. F. Zhou, "Generalized Hawkes Process: Nonparametric and Nonstationary", Ph.D. Thesis. [pdf]

  27. F. Zhou, Y. Zhang, Z. Li, X. Fan, Y. Wang, A. Sowmya, F. Chen, "Hawkes Process with Stochastic Triggering Kernel", PAKDD 2019. [pdf]

  28. F. Zhou, Z. Li, X. Fan, Y. Wang, A. Sowmya, F. Chen, "A Refined MISD Algorithm Based on Gaussian Process Regression", PAKDD 2018. [pdf]

  29. J. Cheng*, Q. Wang*, F. Zhou, L. Li, W. Sun, S. Chen, Y. Dai, Y. Fang, L. Yan, "Development of Electromagnetic Forming NbTi Superconducting Joint", IEEE Transactions on Applied Superconductivity. [pdf]

  30. J. Cheng, F. Zhou, L. Li, C. Cui, W. Sun, Y. Dai, Y. Fang, "Fabrication of NbTi Superconducting Joint by Electromagnetic Forming Method", IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, 2015. [pdf]

  31. J. Cheng*, L. Li, F. Zhou, J. Liu, C. Cui, X. Hu, Y. Dai, L. Yan, S. Cheng, Y. Li, "Contact Resistance Properties of Cold-pressing Superconducting Joints", IEEE Transactions on Applied Superconductivity. [pdf]

  32. F. Zhou*, J. Cheng, Y. Xu, S. Song, Y. Dai, Q. Wang*, "Investigation of Orthogonal Experiment for Fabrication of A Soldering Joint for A 4-T HTS Coil", IEEE Transactions on Applied Superconductivity. [pdf]

  33. F. Zhou*, J. Cheng, Y. Dai, Q. Wang, L. Yan, "Numerical Simulation of Mold Shape’s Influence on NbTi Cold-pressing Superconducting Joint", Physica C: Superconductivity. [pdf]

  34. J. Liu*, J. Cheng, F. Zhou, Q. Wang*, K. Chang, X. Li, "Electrical Properties of Cold-pressing Welded NbTi Persistent Joints", Cryogenics. [pdf]

  35. F. Zhou*, J. Cheng, J. Liu, Y. Dai, Q. Wang*, N. Xiao, L. Yan, "Numerical Simulation of NbTi Superconducting Joint with Cold-pressing Welding Technology", IEEE Transactions on Applied Superconductivity. [pdf]