Phan, B. T. (2019). Bayesian Deep Learning and Uncertainty in Computer Vision Waterloo. Retrieved from http://hdl.handle.net/10012/15056 (Original work published 2019)
References
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2019
Lee, J., Balakrishnan, A., Gaurav, A., Czarnecki, K., & Sedwards, S. (2019). WiseMove: A Framework to Investigate Safe Reinforcement Learning for Autonomous Driving Glasgow, Scotland: Springer.
Phan, B. T., Khan, S., Salay, R., & Czarnecki, K. (2019). Bayesian Uncertainty Quantification with Synthetic Data Presented at the Bayesian Uncertainty Quantification With Synthetic Data conference. Turku, Finland: SAFECOMP. Retrieved from https://www.waise.org/ (Original work published 2019)
Jhunjhunwala, A. (2019). Policy Extraction via Online Q-Value Distillation Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/14963 (Original work published 2019)
Li, C., & Czarnecki, K. (2019). Rethinking Expected Cumulative Reward Formalism of Reinforcement Learning: A Micro-Objective Perspective Presented at the Rethinking Expected Cumulative Reward Formalism of Reinforcement Learning: A Micro-Objective Perspective conference. Montreal.
Ilievski, M., Sedwards, S., Gaurav, A., Balakrishnan, A., Sarkar, A., Lee, J., … Czarnecki, K. (2019). Design Space of Behaviour Planning for Autonomous Driving Waterloo. Retrieved from https://arxiv.org/abs/1908.07931 (Original work published 2019)
Sarkar, A., & Czarnecki, K. (2019). A behavior driven approach for sampling rare event situations for autonomous vehicles Presented at the A Behavior Driven Approach for Sampling Rare Event Situations for Autonomous Vehicles conference. Retrieved from https://ieeexplore.ieee.org/abstract/document/8967715
Juodisius, P., Sarkar, A., Mukkamala, R. R., Antkiewicz, M., Czarnecki, K., & Wąsowski, A. (2019). Clafer: Lightweight Modeling of Structure, Behaviour, and Variability The Art, Science, and Engineering of Programming, 3(1). https://doi.org/https://doi.org/10.22152/programming-journal.org/2019/3/2 (Original work published 2018)
Masud, Z. (2019). Switching GAN-based Image Filters to Improve Perception for Autonomous Driving Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/15228 (Original work published 2019)
Li, C., & Czarnecki, K. (2019). Urban Driving with Multi-Objective Deep Reinforcement Learning Presented at the Urban Driving With Multi-Objective Deep Reinforcement Learning conference. Montreal: IFAAMAS.