Mayur Dhanaraj*, Van Tien Nguyen*, and Panagiotis P. Markopoulos, “Adaptive Low-Rank Multilinear Transformations for Compact Convolutional Neural Networks,” IEEE Transactions on Artificial Intelligence, 2026. Under revision. *Equal contribution. Supported by NSF Grant No. 2332744.
Van Tien Nguyen and Panagiotis P. Markopoulos, “VQBR: Variational Quantum Bayesian Regression via Measurement-Based MAP Direction Recovery,” to appear in Proceedings of the 2026 IEEE International Conference on Quantum Computing and Engineering (QCE), Quantum Machine Learning Technical Papers Track, Toronto, ON, Canada, Sept. 2026. Accepted.
Van Tien Nguyen and Panagiotis P. Markopoulos, “Parameter-Efficient Multilinear Readout for Quantum Reservoir Computing,” Workshop on Quantum Machine Learning at the 2026 IEEE International Conference on Quantum Computing and Engineering (QML@QCE), 2026. Submitted.
Van Tien Nguyen, Mayur Dhanaraj, and Panagiotis P. Markopoulos, “Depth- and Rank-Selective Multilinear Transformation Layers for Compact CNNs,” 60th Asilomar Conference on Signals, Systems, and Computers, 2026. Submitted; Paper #1426, Student Paper Competition.
Van Tien Nguyen and Panagiotis P. Markopoulos, “Quantum-based Tensor Contraction Layers,” in Machine Learning from Challenging Data 2026, Proc. SPIE, Vol. 14030, Paper No. 140300I, 2026. doi:10.1117/12.3098024
M. Tran, T. Pham, V. T. Nguyen, T. Do, and T. N. Duc, “A robust framework for mathematical formula detection,” 2021 International Conference on Multimedia Analysis and Pattern Recognition (MAPR), 2021, pp. 1-6. doi:10.1109/MAPR53640.2021.9585197