Publications

1. Luu, N. T., & Luu, D. T. (2026). FLARE: Forward-only Local Learning via Anticipatory Residual Eligibility for Spiking Neural Networks. In Lecture Notes in Computer Science (pp. 90–101). Springer Nature Singapore. https://doi.org/10.1007/978-981-92-5641-9_8 DOI International
2. Luu, N. T., & Luu, D. T. (2026). HIQI-MLP: Hybrid Interlaced Quantum-Izhikevich Multilayer Perceptron. In Lecture Notes in Computer Science (pp. 15–26). Springer Nature Singapore. https://doi.org/10.1007/978-981-92-5641-9_2 DOI International
3. Trong Luu, N., Trung Luu, D., Ngoc Pham, N., & Cong Truong, T. (2026). Why temporal spike order reversal drops spiking network accuracy and how to partially mitigate it. Neuromorphic Computing and Engineering, 6(3), 034016. https://doi.org/10.1088/2634-4386/ae98af DOI International
4. Luu, N. T., Nguyen, T. Q., Luu, D. T., & Thang, T. C. (2026). Optical Quantum Mixed-State Reconstruction with Multiple Deep Learning Approaches. SN Computer Science, 7(5). https://doi.org/10.1007/s42979-026-05088-0 DOI International
5. Luu, N. T., Luu, D. T., Pham, N. N., & Truong, T. C. (2026). Parameter efficient hybrid spiking-quantum convolutional neural network with surrogate gradient and quantum data-reupload. PeerJ Computer Science, 12, e3554. https://doi.org/10.7717/peerj-cs.3554 DOI International
6. Luu, N. T., Luu, D. T., Pham, N. N., & Truong, T. C. (2026). Modeling quantum neural network gradient with reinforcement learning. The Fortieth Annual Conference on Neural Information Processing Systems (NeurIPS 2026). https://doi.org/10.48550/ARXIV.2609.31066 DOI International
7. Luu, N. T., & Luu, D. T. (2026). Quantifying How Training Gradient Sparsity Affect Spiking Neural Network Accuracy And Robustness. Procedia Computer Science, 289, 117–126. https://doi.org/10.1016/j.procs.2026.08.228 DOI International
8. Luu, N. T., Luu, D. T., Nam, P. N., & Thang, T. C. (2026). Direct-to-Event Spiking Neural Network Transfer. IEEE Signal Processing Letters, 33, 2335–2339. https://doi.org/10.1109/lsp.2026.3692100 DOI International
9. Luu, N. T., Luu, D. T., NAM, P. N., & Thang, T. C. (2026). A Survey on Spiking Neural Network Foundation and Recent Progress. IEEE Access, 14, 78497–78557. https://doi.org/10.1109/access.2026.3685666 DOI International
10. Luu, N. T., Moreaux, T., Khaustov, V., Khaustova, V., Mataar, M., Krueger, T., Raphael, Z. S., Wang, J., Luu, D. T., Nam, P. N., & Thang, T. C. (2026). Robust Reinforcement Learning Quadcopter Control System for Offshore Cement Wind Turbine Construction. IEEE Access, 14, 51918–51942. https://doi.org/10.1109/access.2026.3680347 DOI International
11. Trong Nhan, L., Trung Duong, L., Ngoc Nam, P., & Cong Thang, T. (2025). Improvement of Spiking Neural Network With Bit Planes and Color Models. IEEE Access, 13, 198607–198622. https://doi.org/10.1109/access.2025.3635297 DOI International
12. Luu, N. T., Luu, D. T., Nam, P. N., & Thang, T. C. (2024). Improvement of Spiking Neural Network with Bit Plane Coding. In 2024 IEEE 16th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 1220–1224). IEEE. 2024 IEEE 16th International Conference on Computational Intelligence and Communication Networks (CICN). https://doi.org/10.1109/cicn63059.2024.10847438 DOI International
13. Luu, N. T., Onuoha, C., & Thang, T. C. (2023). Blind Image Quality Assessment With Multimodal Prompt Learning. In 2023 IEEE 15th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 614–618). IEEE. 2023 IEEE 15th International Conference on Computational Intelligence and Communication Networks (CICN). https://doi.org/10.1109/cicn59264.2023.10402183 DOI International
14. Ngo, T. A., Luu, N. T., & Thang, T. C. (2023). An Evaluation of Training Strategies in QuGAN. In 2023 IEEE International Conference on Quantum Computing and Engineering (QCE) (pp. 336–337). IEEE. 2023 IEEE International Conference on Quantum Computing and Engineering (QCE). https://doi.org/10.1109/qce57702.2023.10270 DOI International