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Guo, G., Goldfeder, J., Ray, A., Dear, T. and Lipson, H., 2025. Deepcollide: Scalable data-driven high dof configuration space modeling using implicit neural representations. In Proceedings of the IEEE/CVF International Conference on Computer Vision (pp. 2689-2699). https://openaccess.thecvf.com/content/ICCV2025W/E2E3D/html/Guo_DeepCollide_Scalable_Data-Driven_High_DoF_Configuration_Space_Modeling_using_Implicit_ICCVW_2025_paper.html
Pujari, A., Lin, H., Neal, W.L., Dear, T. and Kelly, S.D., 2023. Detecting and Exploiting Symmetry to Accelerate Reinforcement Learning. In 2023 Proceedings of the Conference on Control and its Applications (CT) (pp. 103-110). Society for Industrial and Applied Mathematics. https://epubs.siam.org/doi/abs/10.1137/1.9781611977745.14
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Grover, J., Zimmer, J., Dear, T., Travers, M., Choset, H. and Kelly, S.D., 2018, June. Geometric motion planning for a three-link swimmer in a three-dimensional low Reynolds-number regime. In 2018 annual american control conference (ACC) (pp. 6067-6074). IEEE. https://ieeexplore.ieee.org/abstract/document/8431828
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