Reference author: Krzysztof Czarnecki

Zulkoski, E. ., Martins, R. ., Wintersteiger, C. ., Robere, R. ., Liang, J. H., Czarnecki, K. ., & Ganesh, V. . (2017). Empirically Relating Complexity-theoretic Parameters with SAT Solver Performance. Empirically Relating Complexity-Theoretic Parameters With SAT Solver Performance. Presented at the. EPIC. (Original work published 2017)

Chauchan, M. ., Pellizzoni, R. ., & Czarnecki, K. . (2017). Modeling the Effects of AUTOSAR Overheads on Application Timing and Schedulability. Modeling the Effects of AUTOSAR Overheads on Application Timing and Schedulability. Presented at the. Retrieved from https://dac.com/2017/accepted-papers (Original work published 2017)

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

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. 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)

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. 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)

Sarkar, A. ., Czarnecki, K. ., Angus, M. ., Li, C. ., & Waslander, S. . (2017). Trajectory prediction of traffic agents at urban intersections through learned interactions.. Trajectory Prediction of Traffic Agents at Urban Intersections through Learned Interactions. Presented at the. 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. Rethinking Expected Cumulative Reward Formalism of Reinforcement Learning: A Micro-Objective Perspective. Presented at the. Montreal.

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