| Deep dispatching: A deep reinforcement learning approach for vehicle dispatching on online ride-hailing platform Y Liu, F Wu, C Lyu, S Li, J Ye, X Qu Transportation Research Part E: Logistics and Transportation Review 161, 102694, 2022 | 70 | 2022 |
| Can language models be used for real-world urban-delivery route optimization? Y Liu, F Wu, Z Liu, K Wang, F Wang, X Qu The Innovation 4 (6), 2023 | 48 | 2023 |
| Wood identification based on longitudinal section images by using deep learning F Wu, R Gazo, E Haviarova, B Benes Wood Science and Technology 55, 553-563, 2021 | 28 | 2021 |
| Traffic4cast at neurips 2020-yet more on the unreasonable effectiveness of gridded geo-spatial processes M Kopp, D Kreil, M Neun, D Jonietz, H Martin, P Herruzo, A Gruca, ... NeurIPS 2020 Competition and Demonstration Track, 325-343, 2021 | 22 | 2021 |
| Behavior2vector: Embedding users’ personalized travel behavior to Vector Y Liu, F Wu, C Lyu, X Liu, Z Liu IEEE Transactions on Intelligent Transportation Systems 23 (7), 8346-8355, 2021 | 19 | 2021 |
| A personalized recommendation system for multi-modal transportation systems F Wu, C Lyu, Y Liu Multimodal transportation 1 (2), 100016, 2022 | 13 | 2022 |
| Efficient project gradient descent for ensemble adversarial attack F Wu, R Gazo, E Haviarova, B Benes arXiv preprint arXiv:1906.03333, 2019 | 10 | 2019 |
| Deep BarkID: a portable tree bark identification system by knowledge distillation F Wu, R Gazo, B Benes, E Haviarova European Journal of Forest Research 140 (6), 1391-1399, 2021 | 9 | 2021 |
| Building effective large-scale traffic state prediction system: Traffic4cast challenge solution Y Liu, F Wu, B Yu, Z Liu, J Ye arXiv preprint arXiv:1911.05699, 2019 | 3 | 2019 |
| DeTiME: Diffusion-enhanced topic modeling using encoder-decoder based LLM W Xu, W Hu, F Wu, S Sengamedu arXiv preprint arXiv:2310.15296, 2023 | 2 | 2023 |
| Some Practice for Improving the Search Results of E-commerce F Wu, Y Liu, R Gazo, B Bedrich, X Qu arXiv preprint arXiv:2208.00108, 2022 | 2 | 2022 |
| Tlab: Traffic map movie forecasting based on HR-NET F Wu, Y Liu, Z Liu, X Qu, R Gazo, E Haviarova arXiv preprint arXiv:2011.07728, 2020 | 2 | 2020 |
| Life-Cycle Inventory of Hardwood Lumber School Chair F Wu, E Haviarova, J Helfrich Department of Forestry and Natural Resources Purdue University, 2018 | 2 | 2018 |
| Sequence-Level Certainty Reduces Hallucination In Knowledge-Grounded Dialogue Generation Y Wan, F Wu, W Xu, SH Sengamedu arXiv preprint arXiv:2310.18794, 2023 | 1 | 2023 |
| Phase transition in a growing network F Wu, PP Kärenlampi Journal of Complex Networks 6 (5), 788-799, 2018 | 1 | 2018 |
| Automated tree ring detection of common Indiana hardwood species through deep learning: Introducing a new dataset of annotated images F Wu, Y Huang, B Benes, CC Warner, R Gazo Information Processing in Agriculture, 2023 | | 2023 |
| International Workshop on Multimodal Learning-2023 Theme: Multimodal Learning with Foundation Models Y Ling, F Wu, S Dong, Y Feng, G Karypis, CK Reddy Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | | 2023 |
| Selected Topics of Deep Learning Application in Forest Research F Wu Purdue University, 2021 | | 2021 |
| Deep Learning for Lumer Identification F Wu, R Gazo, B Benes, E Haviarova | | 2019 |
| Pellet trade assessment in Europe during the period 2008-2015 F Wu Itä-Suomen yliopisto, 2018 | | 2018 |
R GazoForestry and Natural Resources, Purdue UniversityVerified email at purdue.edu
