| A unified framework for automatic wound segmentation and analysis with deep convolutional neural networks C Wang, X Yan, M Smith, K Kochhar, M Rubin, SM Warren, J Wrobel, ... 2015 37th annual international conference of the ieee engineering in …, 2015 | 174 | 2015 |
| No-press diplomacy: Modeling multi-agent gameplay P Paquette, Y Lu, SS Bocco, M Smith, S O-G, JK Kummerfeld, J Pineau, ... Advances in Neural Information Processing Systems 32, 2019 | 65 | 2019 |
| Long term effects of pair programming MO Smith, A Giugliano, A DeOrio IEEE Transactions on Education 61 (3), 187-194, 2017 | 32 | 2017 |
| Iterative empirical game solving via single policy best response MO Smith, T Anthony, MP Wellman International Conference on Learning Representations (ICLR), 2021 | 19 | 2021 |
| Learning to play against any mixture of opponents MO Smith, T Anthony, Y Wang, MP Wellman Frontiers in Artificial Intelligence 6, 2023 | 14 | 2023 |
| Speaker Naming in Movies M Azab, M Wang, M Smith, N Kojima, J Deng, R Mihalcea North American Chapter of the Association for Computational Linguistics …, 2018 | 11 | 2018 |
| Population-based evaluation in repeated rock-paper-scissors as a benchmark for multiagent reinforcement learning M Lanctot, J Schultz, N Burch, MO Smith, D Hennes, T Anthony, J Perolat arXiv preprint arXiv:2303.03196, 2023 | 4 | 2023 |
| Co-Learning Empirical Games and World Models MO Smith, MP Wellman arXiv preprint arXiv:2305.14223, 2023 | 3 | 2023 |
| Strategic knowledge transfer MO Smith, T Anthony, MP Wellman Journal of Machine Learning Research 24 (233), 1-96, 2023 | 3 | 2023 |
| Efficient Game Solving Through Transfer Learning M Smith | | 2023 |
Michael WellmanProfessor of Computer Science & Engineering, University of MichiganBestätigte E-Mail-Adresse bei umich.edu
