| FireCast: Leveraging Deep Learning to Predict Wildfire Spread D Radke, A Hessler, D Ellsworth IJCAI, 4575-4581, 2019 | 110 | 2019 |
| Exploring the Benefits of Teams in Multiagent Learning D Radke, K Larson, T Brecht IJCAI, 2022 | 10 | 2022 |
| The Importance of Credo in Multiagent Learning D Radke, K Larson, T Brecht AAMAS, 2023 | 8 | 2023 |
| Passing and Pressure Metrics in Ice Hockey D Radke, D Radke, T Brecht, A Pawelczyk Artificial Intelligence for Sports Analytics (AISA) Workshop at IJCAI 2021, 2021 | 8 | 2021 |
| Beyond measurement: Extracting vegetation height from high resolution imagery with deep learning D Radke, D Radke, J Radke Remote Sensing 12 (22), 3797, 2020 | 6 | 2020 |
| Identifying Completed Pass Types and Improving Passing Lane Models D Radke, T Brecht, D Radke Linköping Hockey Analytics Conference (LINHAC), 2022 | 5 | 2022 |
| Towards a Better Understanding of Learning with Multiagent Teams D Radke, K Larson, T Brecht, K Tilbury IJCAI, 2023 | 3 | 2023 |
| Presenting Multiagent Challenges in Team Sports Analytics D Radke, A Orchard AAMAS, 2023 | 3 | 2023 |
| Can future wireless networks detect fires? D Radke, O Abari, T Brecht, K Larson Proceedings of the 7th ACM International Conference on Systems for Energy …, 2020 | 2 | 2020 |
| Learning to Learn Group Alignment: A Self-Tuning Credo Framework with Multiagent Teams D Radke, K Tilbury Adaptive and Learning Agents (ALA) Workshop at AAMAS, 2023 | 1 | 2023 |
| An Analysis of Engineering Students’ Responses to an AI Ethics Scenario A Orchard, D Radke EAAI, 2023 | 1 | 2023 |
| The Impact of Teams in Multiagent Systems D Radke University of Waterloo, 2023 | | 2023 |
| Analyzing Passing Metrics in Ice Hockey using Puck and Player Tracking Data D Radke, J Lu, TL Jackson Woloschuk, D Radke, C Liu, T Brecht Linköping Hockey Analytics Conference (LINHAC), 2023 | | 2023 |
Tim BrechtUniversity of WaterlooVerified email at uwaterloo.ca
