Vernekar, S., Gaurav, A., Abdelzad, V., Denouden, T., Salay, R., & Czarnecki, K. (2019). Out-of-distribution Detection in Classifiers via Generation Presented at the Out-of-Distribution Detection in Classifiers via Generation conference. https://sites.google.com/view/neurips19-safe-robust-workshop. Retrieved from https://drive.google.com/file/d/0B3mY6u_lryzdel9WOW1XTVA0aDIwazJDcG9ORlZrZWFOd0xJ/view (Original work published 2019)
References
Filter by:
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)
Kothig, A., Ilievski, M., Grasse, L., Rea, F., & Tata, M. (2019). A Bayesian System for Noise-Robust Binaural Sound Localisation for Humanoid Robots Presented at the A Bayesian System for Noise-Robust Binaural Sound Localisation for Humanoid Robots conference. IEEE. https://doi.org/10.1109/ROSE.2019.8790411 (Original work published 2019)
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)
Babaee, R., Ganesh, V., & Sedwards, S. (2019). Accelerated Learning of Predictive Runtime Monitors for Rare Failure Porto, Portugal: Springer.
Khan, S., Phan, B. T., Salay, R., & Czarnecki, K. (2019). ProcSy: Procedural Synthetic Dataset Generation Towards Influence Factor Studies Of Semantic Segmentation Networks Presented at the ProcSy: Procedural Synthetic Dataset Generation Towards Influence Factor Studies Of Semantic Segmentation Networks conference. Long Beach, California, USA: IEEE. Retrieved from https://bit.ly/2G3MA1P (Original work published 2019)
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)
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)
Hurl, B. (2019). Local and Cooperative Autonomous Vehicle Perception from Synthetic Datasets Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/15118 (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.