The QML (Quantum Machine Learning) Research group of AIML (Australian Insitute for Machine Learning), is based since 2020 at the University of Adelaide, South Australia.
Dr Michele Sasdelli
Main contact
(see researcher profile)
Prof Tat-Jun Chin
Dr Dzung Doan
Frances Yang
PhD student
ALUMNI
Cameron McLeod (Master's graduate)
McLeod, C. R., & Sasdelli, M. (2022). Benchmarking D-Wave Quantum Annealers: Spectral Gap Scaling of Maximum Cardinality Matching Problems. In International Conference on Computational Science (pp. 150-163). Springer, Cham. https://doi.org/10.1007/978-3-031-08760-8_13 ; PDF Doan, A. D., Sasdelli, M., Suter, D., & Chin, T. J. (2022). A hybrid quantum-classical algorithm for robust fitting. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 417-427). PDF Sasdelli, M., & Chin, T. J. (2021). Quantum annealing formulation for binary neural networks. In 2021 Digital Image Computing: Techniques and Applications (DICTA) (pp. 1-10). IEEE. PDF Chin, T. J., Suter, D., Ch'ng, S. F., & Quach, J. (2020). Quantum robust fitting. In Proceedings of the Asian Conference on Computer Vision. PDF HONOURS AND AWARDSDST Best Contribution to Science Award (DICTA 2021) Cameron Mcleod: Best Computer Science Presentation Award, Ingenuity 2021. |