Reference author: Krzysztof Czarnecki

Queiroz, R., Passos, L., Valente, M. T., Hunsen, C., Apel, S., & Czarnecki, K. (2017). The shape of feature code: an analysis of twenty C-preprocessor-based systems Software \& Systems Modeling, 16, 96. https://doi.org/10.1007/s10270-015-0483-z (Original work published 2017)

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)

Ross, J., Murashkin, A., Liang, J. H., Antkiewicz, M., & Czarnecki, K. (2017). Synthesis and Exploration of Multi-Level, Multi-Perspective Architectures of Automotive Embedded Systems Software and Systems Modeling. https://doi.org/10.1007/s10270-017-0592-y

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)

Sarkar, A., Czarnecki, K., Angus, M., Li, C., & Waslander, S. (2017). Trajectory prediction of traffic agents at urban intersections through learned interactions. Presented at the Trajectory Prediction of Traffic Agents at Urban Intersections through Learned Interactions. conference. Retrieved from https://ieeexplore.ieee.org/document/8317731

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.

Valov, P., Petkovich, J.-C., Guo, J., Fischmeister, S., & Czarnecki, K. (2017). Transferring Performance Prediction Models Across Different Hardware Platforms Presented at the Transferring Performance Prediction Models Across Different Hardware Platforms conference. https://doi.org/10.1145/3030207.3030216 (Original work published 2017)

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.

Guo, J., Blais, E., Czarnecki, K., & van Beek, P. (2017). A Worst-Case Analysis of Constraint-Based Algorithms for Exact Multi-objective Combinatorial Optimization Presented at the A Worst-Case Analysis of Constraint-Based Algorithms for Exact Multi-Objective Combinatorial Optimization conference. https://doi.org/10.1007/978-3-319-57351-9_16 (Original work published 2017)

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.