Publications

^†Corresponding author. For the complete record see Google Scholar.

1. Fractional-order spiking neural network.
   C. Ge, Y. Peng, Z. Li, Q. Kang^†, X. Fu, X. Li, Q. Zhang, J. Ren, Z. Zha.
   Proc. International Conference on Learning Representations (ICLR) — Rio de Janeiro, Brazil, Apr. 2026.
2. Hierarchical information embeddings with neural ODEs for personalized federated learning.
   R. She, S. Wang, Q. Kang, K. Zhao, T. Geng, Y. Zhao, W. Liang, W. P. Tay.
   IEEE Transactions on Pattern Analysis and Machine Intelligence, in press.
3. Generalized fractional neural differential equation network.
   Q. Kang, W. Cui, X. Li, Y. Li, Y. Ma, X. Fu, W. P. Tay, Z. Zha.
   Advances in Neural Information Processing Systems (NeurIPS) — Vancouver, Canada, Dec. 2025.
4. Multi-modal aerial-ground cross-view place recognition with neural ODEs.
   S. Wang, R. She, Q. Kang, S. Li, D. Li, T. Geng, S. Yu, W. P. Tay.
   Proc. IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR) — Nashville, TN, USA, Jun. 2025.
5. Efficient training of neural fractional-order differential equation via adjoint backpropagation.
   Q. Kang, X. Li, K. Zhao, W. Cui, Y. Zhao, W. Deng, W. P. Tay.
   Proc. AAAI Conference on Artificial Intelligence (AAAI) — Philadelphia, USA, Feb. 2025.
6. Neural variable-order fractional differential equation network.
   W. Cui, Q. Kang, X. Li, K. Zhao, W. P. Tay, W. Deng, Y. Li.
   Proc. AAAI Conference on Artificial Intelligence (AAAI) — Philadelphia, USA, Feb. 2025.
7. Machine learning-based multi-objective optimization framework for industrial black nickel electroplating.
   J. Ren, Q. Kang, S. Feng, Y. Sun, Y.-T. Tan, G. Xiao.
   Journal of Intelligent Manufacturing, pp. 1–17, Feb. 2025.
8. Distributed-order fractional graph operating network. Spotlight
   K. Zhao, X. Li, Q. Kang^†, F. Ji, Q. Ding, Y. Zhao, W. Liang, W. P. Tay.
   Advances in Neural Information Processing Systems (NeurIPS) — Vancouver, Canada, Dec. 2024.
9. PRFusion: Effective and robust multi-modal place recognition with image and point-cloud fusion.
   S. Wang, Q. Kang, R. She, K. Zhao, Y. Song, W. P. Tay.
   IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 12, pp. 20523–20534, 2024.
10. Unleashing the potential of fractional calculus in graph neural networks with FROND. Spotlight
    Q. Kang^†, K. Zhao, Q. Ding, F. Ji, X. Li, W. Liang, Y. Song, W. P. Tay.
    Proc. International Conference on Learning Representations (ICLR) — Vienna, Austria, May 2024.
11. PointDifformer: Robust point-cloud registration with neural diffusion and transformer.
    R. She, Q. Kang, S. Wang, W. P. Tay, K. Zhao, Y. Song, T. Geng, Y. Xu, D. N. Navarro, A. Hartmannsgruber.
    IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1–15, 2024.
12. Coupling graph neural networks with fractional-order continuous dynamics: a robustness study.
    Q. Kang, K. Zhao, Y. Song, Y. Xie, Y. Zhao, S. Wang, R. She, W. P. Tay.
    Proc. AAAI Conference on Artificial Intelligence (AAAI) — Vancouver, Canada, Feb. 2024.
13. PosDiffNet: Positional neural diffusion for point-cloud registration in a large field of view with perturbations.
    R. She, S. Wang, Q. Kang^†, K. Zhao, Y. Song, W. P. Tay, T. Geng, X. Jian.
    Proc. AAAI Conference on Artificial Intelligence (AAAI) — Vancouver, Canada, Feb. 2024.
14. DistilVPR: Cross-modal knowledge distillation for visual place recognition.
    S. Wang, R. She, Q. Kang^†, X. Jian, K. Zhao, Y. Song, W. P. Tay.
    Proc. AAAI Conference on Artificial Intelligence (AAAI) — Vancouver, Canada, Feb. 2024.
15. Multi-armed linear bandits with latent biases.
    Q. Kang^†, W. P. Tay, R. She, S. Wang, X. Liu, Y. Yang.
    Information Sciences, 2024.
16. Adversarial robustness in graph neural networks: a Hamiltonian approach. Spotlight
    K. Zhao, Q. Kang^†, Y. Song, R. She, S. Wang, W. P. Tay.
    Advances in Neural Information Processing Systems (NeurIPS) — New Orleans, USA, Dec. 2023.
17. Node embedding from neural Hamiltonian orbits in graph neural networks.
    Q. Kang^†, K. Zhao, Y. Song, S. Wang, W. P. Tay.
    Proc. International Conference on Machine Learning (ICML) — Hawaii, USA, Jul. 2023.
18. Graph neural convection-diffusion with heterophily.
    K. Zhao, Q. Kang, Y. Song, R. She, S. Wang, W. P. Tay.
    Proc. International Joint Conference on Artificial Intelligence (IJCAI) — Macao, China, Aug. 2023.
19. HypLiLoc: Effective LiDAR pose regression with hyperbolic fusion.
    S. Wang, Q. Kang, R. She, W. Wang, K. Zhao, Y. Song, W. P. Tay.
    Proc. IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR) — Vancouver, Canada, Jun. 2023.
20. RobustLoc: Robust camera pose regression in challenging driving environments.
    S. Wang, Q. Kang, R. She, W. P. Tay, A. Hartmannsgruber, D. N. Navarro.
    Proc. AAAI Conference on Artificial Intelligence (AAAI) — Washington, USA, Feb. 2023.
21. RobustMat: Neural diffusion for street landmark patch matching under challenging environments.
    R. She, Q. Kang, S. Wang, Y. Yang, K. Zhao, Y. Song, W. P. Tay.
    IEEE Transactions on Image Processing, 2023.
22. Image patch-matching with graph-based learning in street scenes.
    R. She, Q. Kang^†, S. Wang, W. P. Tay, Y. L. Guan, D. N. Navarro, A. Hartmannsgruber.
    IEEE Transactions on Image Processing, vol. 32, pp. 3465–3480, 2023.
23. Unleashing the potential of fractional calculus in graph neural networks.
    Q. Kang, K. Zhao, Q. Ding, F. Ji, X. Li, W. Liang, Y. Song, W. P. Tay.
    NeurIPS 2023 Workshop on Machine Learning and the Physical Sciences.
24. Advancing graph neural networks through joint time-space dynamics.
    Q. Kang, Y. Zhao, K. Zhao, X. Li, Q. Ding, W. P. Tay, S. Wang.
    NeurIPS 2023 Workshop on Deep Learning and Differential Equations.
25. Image patch-matching with graph-based learning in street scenes.
    R. She, Q. Kang, S. Wang, K. Zhao, Y. Song, Y. Xu, T. Geng, W. P. Tay, D. N. Navarro, A. Hartmannsgruber.
    Proc. IEEE International Conference on Image Processing (ICIP) — invited paper, Kuala Lumpur, Malaysia, Oct. 2023.
26. On the robustness of graph neural diffusion to topology perturbations.
    Y. Song, Q. Kang, S. Wang, K. Zhao, W. P. Tay.
    Advances in Neural Information Processing Systems (NeurIPS) — New Orleans, USA, Nov. 2022.
27. Task recommendation in crowdsourcing based on learning preferences and reliabilities.
    Q. Kang, W. P. Tay.
    IEEE Transactions on Services Computing, vol. 15, no. 4, pp. 1785–1798, 2022.
28. Location learning for AVs: LiDAR and image landmarks fusion localization with graph neural networks.
    Q. Kang, R. She, S. Wang, W. P. Tay, N. D. Navarro, R. Khurana, A. Hartmannsgruber.
    Proc. IEEE International Conference on Intelligent Transportation Systems (ITSC) — Macau, China, Oct. 2022.
29. Stable neural ODE with Lyapunov-stable equilibrium points for defending against adversarial attacks.
    Q. Kang, Y. Song, Q. Ding, W. P. Tay.
    Advances in Neural Information Processing Systems (NeurIPS) — virtual, Dec. 2021.
30. Error-correcting output codes with ensemble diversity for robust learning in neural networks.
    Y. Song, Q. Kang, W. P. Tay.
    Proc. AAAI Conference on Artificial Intelligence (AAAI) — virtual, Feb. 2021.
31. Sequential multi-class labeling in crowdsourcing.
    Q. Kang, W. P. Tay.
    IEEE Transactions on Knowledge and Data Engineering, vol. 31, no. 11, pp. 2190–2199, Nov. 2019.
32. Orthogonal projection in linear bandits.
    Q. Kang, W. P. Tay.
    Proc. IEEE Global Conference on Signal and Information Processing (GlobalSIP) — Ottawa, Canada, Nov. 2019.
33. Sequential multi-class labeling in crowdsourcing: a Ulam-Renyi game approach.
    Q. Kang, W. P. Tay.
    IEEE/WIC/ACM International Conference on Web Intelligence — Leipzig, Germany, Aug. 2017.