| Guiding GBFS through learned pairwise rankings M Hao, F Trevizan, S Thiébaux, P Ferber, J Hoffmann Thirty-Third International Joint Conference on Artificial Intelligence …, 2024 | 6 | 2024 |
| Blockchain-enabled parametric solar energy insurance via remote sensing M Hao, K Qian, SCK Chau Proceedings of the 14th ACM International Conference on Future Energy …, 2023 | 4 | 2023 |
| Action Schema Networks–IPC Version M Hao, S Toyer, R Wang, S Thiébaux, F Trevizan Tenth International Planning Competition (IPC-10) Learning Track: Planner …, 2023 | 3 | 2023 |
| Learning to predict short-term volatility with order flow image representation A Lensky, M Hao 2024 IEEE Conference on Artificial Intelligence (CAI), 817-822, 2024 | 2 | 2024 |
| Learned Pairwise Rankings for Greedy Best-First Search M Hao, F Trevizan, S Thiébaux, P Ferber, J Hoffmann Proc. ICAPS Workshop on Reliable Data-Driven Planning and Scheduling, 2024 | 2 | 2024 |
| Privacy-preserving Blockchain-enabled Parametric Insurance via Remote Sensing and IoT M Hao, K Qian, SCK Chau arXiv preprint arXiv:2305.08384, 2023 | 2 | 2023 |
| Short-Term Volatility Prediction Using Deep CNNs Trained on Order Flow M Hao, A Lenskiy arXiv e-prints, arXiv: 2304.02472, 2023 | 1 | 2023 |
| Graph Learning for Planning: The Story Thus Far and Open Challenges DZ Chen, M Hao, S Thiébaux, F Trevizan arXiv preprint arXiv:2412.02136, 2024 | | 2024 |
