Balakrishnan, A. (2020). Closing the Modelling Gap: Transfer Learning from a Low-Fidelity Simulator for Autonomous Driving Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/15570 (Original work published 2020)
References
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2020
Gaurav, A., Vernekar, S., Lee, J., Sedwards, S., Abdelzad, V., & Czarnecki, K. (2020). Simple Continual Learning Strategies for Safer Classifers Presented at the Simple Continual Learning Strategies for Safer Classifers conference. CEUR. Retrieved from http://ceur-ws.org/Vol-2560/paper6.pdf (Original work published 2020)
Budde, C., D’Argenio, P., Hartmanns, A., & Sedwards, S. (2020). An Efficient Statistical Model Checker for Nondeterminism and Rare Events International Journal on Software Tools For Technology Transfer, Special Issue TACAS 2018.
2019
Angus, M. (2019). Towards Pixel-Level OOD Detection for Semantic Segmentation Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/15004 (Original work published 2019)
De Iaco, R., Smith, S. L., & Czarnecki, K. (2019). Learning a Lattice Planner Control Set for Autonomous Vehicles Presented at the Learning a Lattice Planner Control Set for Autonomous Vehicles conference. Paris, France. https://doi.org/10.1109/IVS.2019.8813797
Deng, J. (2019). MLOD: A multi-view 3D object detection based on robust feature fusion method Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/15086 (Original work published 2019)
Ernst, G., Sedwards, S., Zhang, Z., & Hasuo, I. (2019). Fast Falsification of Hybrid Systems using Probabilistically Adaptive Input Glasgow, Scotland: Springer.
Vernekar, S., Gaurav, A., Denouden, T., Phan, B. T., Abdelzad, V., Salay, R., & Czarnecki, K. (2019). Analysis of Confident-Classifiers for Out-of-Distribution Detection Presented at the Analysis of Confident-Classifiers for Out-of-Distribution Detection conference. Retrieved from https://drive.google.com/uc?export=download\&id=1AY0zFvQ_u1UmGcn0bHs1XCWX9QncaqvT (Original work published 2019)
Li, C. (2019). Autonomous Driving: A Multi-Objective Deep Reinforcement Learning Approach Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/14697 (Original work published 2019)
Khan, S. (2019). Towards Synthetic Dataset Generation for Semantic Segmentation Networks Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/15128 (Original work published 2019)