Li, C. ., & Czarnecki, K. . (2019). Rethinking Expected Cumulative Reward Formalism of Reinforcement Learning: A Micro-Objective Perspective. Rethinking Expected Cumulative Reward Formalism of Reinforcement Learning: A Micro-Objective Perspective. Presented at the. Montreal.
Publications
Filter by:
Sarkar, A. ., & Czarnecki, K. . (2019). A behavior driven approach for sampling rare event situations for autonomous vehicles. A Behavior Driven Approach for Sampling Rare Event Situations for Autonomous Vehicles. Presented at the. Retrieved from https://ieeexplore.ieee.org/abstract/document/8967715
Li, C. ., & Czarnecki, K. . (2019). Urban Driving with Multi-Objective Deep Reinforcement Learning. Urban Driving With Multi-Objective Deep Reinforcement Learning. Presented at the. Montreal: IFAAMAS.
Queiroz, R. ., Berger, T. ., & Czarnecki, K. . (2019). GeoScenario: An Open DSL for Autonomous Driving Scenario Representation. GeoScenario: An Open DSL for Autonomous Driving Scenario Representation. Presented at the. Paris: IEEE.
De Iaco, R. ., Smith, S. L., & Czarnecki, K. . (2019). Learning a Lattice Planner Control Set for Autonomous Vehicles. Learning a Lattice Planner Control Set for Autonomous Vehicles. Presented at the. Paris, France. https://doi.org/10.1109/IVS.2019.8813797
Vernekar, S. ., Gaurav, A. ., Abdelzad, V. ., Denouden, T. ., Salay, R. ., & Czarnecki, K. . (2019). Out-of-distribution Detection in Classifiers via Generation. Out-of-Distribution Detection in Classifiers via Generation. Presented at the. https://sites.google.com/view/neurips19-safe-robust-workshop. Retrieved from https://drive.google.com/file/d/0B3mY6u_lryzdel9WOW1XTVA0aDIwazJDcG9ORlZrZWFOd0xJ/view (Original work published 2019)
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. Analysis of Confident-Classifiers for Out-of-Distribution Detection. Presented at the. Retrieved from https://drive.google.com/uc?export=download\&id=1AY0zFvQ_u1UmGcn0bHs1XCWX9QncaqvT (Original work published 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.
Khan, S. ., Phan, B. T., Salay, R. ., & Czarnecki, K. . (2019). ProcSy: Procedural Synthetic Dataset Generation Towards Influence Factor Studies Of Semantic Segmentation Networks. ProcSy: Procedural Synthetic Dataset Generation Towards Influence Factor Studies Of Semantic Segmentation Networks. Presented at the. Long Beach, California, USA: IEEE. Retrieved from https://bit.ly/2G3MA1P (Original work published 2019)
Phan, B. T., Khan, S. ., Salay, R. ., & Czarnecki, K. . (2019). Bayesian Uncertainty Quantification with Synthetic Data. Bayesian Uncertainty Quantification With Synthetic Data. Presented at the. Turku, Finland: SAFECOMP. Retrieved from https://www.waise.org/ (Original work published 2019)