Export 75 results:
2020
Chen, W. Tao, "Accelerating the Training of Convolutional Neural Networks for Image Segmentation with Deep Active Learning", Computer Science, vol. MMath, Waterloo, University of Waterloo, 01/2020.
Denouden, T., "An Application of Out-of-Distribution Detection for Two-Stage Object Detection Networks", Computer Science, vol. MMath, Waterloo, University of Waterloo, 02/2020.
Chen, H., R. Cohen, K. Dautenhahn, E. Law, and K. Czarnecki, "Autonomous Vehicle Visual Signals for Pedestrians: Experiments and Design Recommendations", The 31st IEEE Intelligent Vehicles Symposium, 2020.
Chen, H., "Autonomous Vehicles with Visual Signals for Pedestrians: Experiments and Design Recommendations", Computer Science, vol. MMath, Waterloo, University of Waterloo, 01/2020.
Pitropov, M., D. Garcia, J. Rebello, M. Smart, C. Wang, K. Czarnecki, and S. Waslander, "Canadian Adverse Driving Conditions Dataset", Computer Vision and Pattern Recognition: arXiv, 01/2020.
Balakrishnan, A., "Closing the Modelling Gap: Transfer Learning from a Low-Fidelity Simulator for Autonomous Driving", Computer Science, vol. MMath, Waterloo, University of Waterloo, 01/2020.
Budde, C., P. D'Argenio, A. Hartmanns, and S. Sedwards, "An Efficient Statistical Model Checker for Nondeterminism and Rare Events", International Journal on Software Tools For Technology Transfer, vol. Special Issue TACAS 2018, 2020. PDF icon PDF (1.06 MB)
Jhunjhunwala, A., J. Lee, S. Sedwards, V. Abdelzad, and K. Czarnecki, "Improved Policy Extraction via Online Q-Value Distillation", The International Joint Conference on Neural Networks (IJCNN), Glasgow, IEEE, 2020.
Dillen, N., M. Ilievski, E. Law, L. E. Nacke, K. Czarnecki, and O. Schneider, "Keep Calm and Ride Along: Passenger Comfort and Anxiety as Physiological Responses to Autonomous Driving Styles", 2020 CHI Conference on Human Factors in Computing Systems: ACM, 04/2020.
Antkiewicz, M., M. Kahn, M. Ala, K. Czarnecki, P. Wells, A. Acharya, and S. Beiker, "Modes of Automated Driving System Scenario Testing: Experience Report and Recommendations", SAE World Congress Experience: SAE, 2020.
Salay, R., K. Czarnecki, I. Alvarez, M. Soledad Elli, S. Sedwards, and J. Weast, "PURSS: Towards Perceptual Uncertainty Aware Responsibility Sensitive Safety with ML", AAAI Workshop on Artificial Intelligence Safety (SafeAI), New York, CEUR, 2020. PDF icon PDF (507.82 KB)
Gaurav, A., "Safety-Oriented Stability Biases for Continual Learning", Computer Science, vol. MMath, Waterloo, University of Waterloo, 01/2020.
Gaurav, A., S. Vernekar, J. Lee, S. Sedwards, V. Abdelzad, and K. Czarnecki, "Simple Continual Learning Strategies for Safer Classifers", Workshop on Artificial Intelligence Safety (SafeAI 2020): CEUR, 02/2020. PDF icon PDF (612.43 KB)
Vernekar, S., "Training Reject-Classifiers for Out-of-distribution Detection via Explicit Boundary Sample Generation", Computer Science, vol. MMath, Waterloo, University of Waterloo, 01.2020.
Valov, P., "Transferring Pareto Frontiers across Heterogeneous Hardware Environments", Computer Science, vol. PhD, Waterloo, University of Waterloo, pp. 119, 09/2020.
Ilievski, M., "WiseBench: A Motion Planning Benchmarking Framework for Autonomous Vehicles", Computer Science, vol. MMath, Waterloo, University of Waterloo, 10/2020.
2019
Balasubramanian, V., "3D Online Multi-Object Tracking for Autonomous Driving", Computer Science, vol. MMath, Waterloo, University of Waterloo, 08/2019.
Babaee, R., V. Ganesh, and S. Sedwards, "Accelerated Learning of Predictive Runtime Monitors for Rare Failure", 19th International Conference on Runtime Verification (RV 2019), Porto, Portugal, Springer, 2019.
Vernekar, S., A. Gaurav, T. Denouden, B. Truong Phan, V. Abdelzad, R. Salay, and K. Czarnecki, "Analysis of Confident-Classifiers for Out-of-Distribution Detection", Safe Machine Learning, ICLR 2019 Workshop, 05/2019.
Li, C., "Autonomous Driving: A Multi-Objective Deep Reinforcement Learning Approach", Electrical and Computer Engineering, vol. MASc, Waterloo, University of Waterloo, 05/2019.
Chao, E., "Autonomous Driving: Mapping and Behavior Planning for Crosswalks", Electrical and Computer Engineering, vol. MASc, Waterloo, University of Waterloo, 09/2019.
Phan, B. Truong, "Bayesian Deep Learning and Uncertainty in Computer Vision", Electrical and Computer Engineering, vol. MASc, Waterloo, University of Waterloo, 09/2019.
Kothig, A., M. Ilievski, L. Grasse, F. Rea, and M. Tata, "A Bayesian System for Noise-Robust Binaural Sound Localisation for Humanoid Robots", 2019 IEEE International Symposium on Robotic and Sensors Environments (ROSE): IEEE, 08/2019.
Phan, B. Truong, S. Khan, R. Salay, and K. Czarnecki, "Bayesian Uncertainty Quantification with Synthetic Data", WAISE 2019 : Second International Workshop on Artificial Intelligence Safety Engineering, Turku, Finland, SAFECOMP, 09/2019. PDF icon waise.pdf (5.37 MB)
Ilievski, M., S. Sedwards, A. Gaurav, A. Balakrishnan, A. Sarkar, J. Lee, F. Bouchard, R. De Iaco, and K. Czarnecki, Design Space of Behaviour Planning for Autonomous Driving, Waterloo, University of Waterloo, 08.2019.
Ernst, G., S. Sedwards, Z. Zhang, and I. Hasuo, "Fast Falsification of Hybrid Systems using Probabilistically Adaptive Input", 16th International Conference on Quantitative Evaluation of Systems (QEST 2019), Glasgow, Scotland, Springer, 2019.
Queiroz, R., T. Berger, and K. Czarnecki, "GeoScenario: An Open DSL for Autonomous Driving Scenario Representation", IEEE Intelligent Vehicles Symposium (IV), Paris, IEEE, 2019. PDF icon iv2019_0501_fi.pdf (3.77 MB)
De Iaco, R., S. L. Smith, and K. Czarnecki, "Learning a Lattice Planner Control Set for Autonomous Vehicles", IEEE Intelligent Vehicles Symposium (IV), Paris, France, 2019. PDF icon ieee_iv_llp_copy.pdf (1.89 MB)
Hurl, B., "Local and Cooperative Autonomous Vehicle Perception from Synthetic Datasets", Computer Science, vol. MMath, Waterloo, University of Waterloo, 09/2019.
Deng, J., "MLOD: A multi-view 3D object detection based on robust feature fusion method", Computer Science, vol. MMath, Waterloo, University of Waterloo, 09/2019.
De Iaco, R., "Motion Planning and Safety for Autonomous Driving", Electrical and Computer Engineering, vol. MASc, Waterloo, University of Waterloo, 12/2019.
Vernekar, S., A. Gaurav, V. Abdelzad, T. Denouden, R. Salay, and K. Czarnecki, "Out-of-distribution Detection in Classifiers via Generation", Neural Information Processing Systems (NeurIPS 2019), Safety and Robustness in Decision Making Workshop: https://sites.google.com/view/neurips19-safe-robust-workshop, 12/2019.
Dillen, N., "Passenger Response to Driving Style in an Autonomous Vehicle", Computer Science, vol. MMath, Waterloo, University of Waterloo, 09/2019.
Jhunjhunwala, A., "Policy Extraction via Online Q-Value Distillation", Computer Science, vol. MMath, Waterloo, University of Waterloo, 08/2019.
Khan, S., B. Truong Phan, R. Salay, and K. Czarnecki, "ProcSy: Procedural Synthetic Dataset Generation Towards Influence Factor Studies Of Semantic Segmentation Networks", Vision for All Seasons: Bad Weather and Nighttime (CVPR'19 Workshop), Long Beach, California, USA, IEEE, 06/2019. PDF icon procsy_cvpr (986.4 KB)
Li, C., and K. Czarnecki, "Rethinking Expected Cumulative Reward Formalism of Reinforcement Learning: A Micro-Objective Perspective", Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM), Montreal, 2019.
Masud, Z., "Switching GAN-based Image Filters to Improve Perception for Autonomous Driving", Computer Science, vol. MMath, Waterloo, University of Waterloo, 10/2019.
Jaeger, M., P. G. Jensen, K. G. Larsen, A. Legay, S. Sedwards, and J. H. Taankvist, "Teaching Stratego to Play Ball: Optimizing Continuous Space MDPs", 17th International Symposium on Automated Technology for Verification and Analysis (ATVA 2019), Taipei, Taiwan, Springer, 2019.
Angus, M., "Towards Pixel-Level OOD Detection for Semantic Segmentation", Computer Science, vol. MMath, Waterloo, University of Waterloo, 08/2019.
Khan, S., "Towards Synthetic Dataset Generation for Semantic Segmentation Networks", Electrical and Computer Engineering, vol. MASc, Waterloo, University of Waterloo, 09/2019.
Li, C., and K. Czarnecki, "Urban Driving with Multi-Objective Deep Reinforcement Learning", International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Montreal, IFAAMAS, 2019.
Lee, J., A. Balakrishnan, A. Gaurav, K. Czarnecki, and S. Sedwards, "WiseMove: A Framework to Investigate Safe Reinforcement Learning for Autonomous Driving", 16th International Conference on Quantitative Evaluation of Systems (QEST 2019), Glasgow, Scotland, Springer, 2019.
2018
Colwell, I., B. Truong Phan, S. Saleem, R. Salay, and K. Czarnecki, "An Automated Vehicle Safety Concept Based on Runtime Restriction of the Operational Design Domain", The 2018 IEEE Intelligent Vehicles Symposium, 2018. PDF icon restricted_operational_domain.pdf (402.55 KB)
Kido, K., S. Sedwards, and I. Hasuo, "Bounding Errors Due to Switching Delays in Incrementally Stable Switched Systems", 6th Conference on Analysis and Design of Hybrid Systems (ADHS 2018), 16, vol. 51, Oxford, United Kingdom, Elsevier, pp. 247–252, 2018.
Phan, B. Truong, R. Salay, K. Czarnecki, V. Abdelzad, T. Denouden, and S. Vernekar, "Calibrating Uncertainties in Object Localization Task", Third workshop on Bayesian Deep Learning (NeurIPS 2018), Montréal, Canada., 12/2018. PDF icon bdl_workshop_82.pdf (357.72 KB)
Juodisius, P., A. Sarkar, R. Rao Mukkamala, M. Antkiewicz, K. Czarnecki, and A. Wąsowski, "Clafer: Lightweight Modeling of Structure and Behaviour", The Art, Science, and Engineering of Programming Journal, vol. 3, issue 1, 07/2018. Package icon PowerWindow example in Clafer (3.45 KB)Package icon PowerWindow example in AADL (12.36 KB)Package icon PowerWindow example in Live Sequence Charts (51.75 KB)Package icon PowerWindow example in SysML (413.76 KB)Package icon PowerWindow example in Temporal OCL (9.27 KB)
Zayan, D., A. Sarkar, M. Antkiewicz, R. Suzana Pit Maciel, and K. Czarnecki, "Example-driven modeling: on effects of using examples on structural model comprehension, what makes them useful, and how to create them", Software & Systems Modeling, 01/2018.
Given-Wilson, T., A. Legay, S. Sedwards, and O. Zendra, "Group abstraction for assisted navigation of social activities in intelligent environments", Springer Journal of Reliable Intelligent Environments, vol. 4, issue 2, pp. 107–120, 2018.
D'Argenio, P., M. Gerhold, A. Hartmanns, and S. Sedwards, "A Hierarchy of Scheduler Classes for Stochastic Automata", 21st International Conference on Foundations of Software Science and Computation Structures (FoSSaCS 2018), vol. 10803, Thessaloniki, Greece, Springer, pp. 384–402, 2018.
D'Argenio, P., A. Hartmanns, and S. Sedwards, "Lightweight Statistical Model Checking in Nondeterministic Continuous Time", 9th International Symposium on Leveraging Applications (ISoLA 2018), vol. 11245, Limassol, Cyprus, Springer, pp. 336–353, 2018.
Liang, J. Hui, "Machine Learning for SAT Solvers", Electrical and Computer Engineering, vol. Doctor of Philosophy, Waterloo, ON, Canada, University of Waterloo, 12/2018.
Colwell, I., "Runtime Restriction of the Operational Design Domain: A Safety Concept for Automated Vehicles", Electrical and Computer Engineering, vol. MASc, Waterloo, University of Waterloo, 06/2018.
Budde, C., P. D'Argenio, A. Hartmanns, and S. Sedwards, "A Statistical Model Checker for Nondeterminism and Rare Events", 24th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2018), vol. 10806, pp. 340–358, 2018.
Passos, L., R. Queiroz, M. Mukelabai, T. Berger, S. Apel, K. Czarnecki, and J. Alejandro Padilla, "A Study of Feature Scattering in the Linux Kernel", IEEE Transactions on Software Engineering, 2018.
Zhang, Z., G. Ernst, I. Hasuo, and S. Sedwards, "Time-Staging Enhancement of Hybrid System Falsification", IEEE Workshop on Monitoring and Testing of Cyber-Physical Systems (MT-CPS 2018), Porto, Portugal, IEEE, pp. 3–4, 2018.
Czarnecki, K., and R. Salay, "Towards a Framework to Manage Perceptual Uncertainty for Safe Automated Driving", International Workshop on Artificial Intelligence Safety Engineering (WAISE), Västerås, Sweden, Springer, 09/2018. PDF icon paper.pdf (323.45 KB)
Zhang, Z., G. Ernst, S. Sedwards, P. Arcani, and I. Hasuo, "Two-Layered Falsification of Hybrid Systems Guided by Monte Carlo Tree Search. IEEE TCAD", ACM International Conference on Embedded Software (EMSOFT 2018), 11, vol. 37, Torino, Italy, IEEE, pp. 2894–2905, 2018.
Zulkoski, E., "Understanding and Enhancing CDCL-based SAT Solvers", Computer Science, vol. PhD, Waterloo, University of Waterloo, 08/2018.
Angus, M., M. ElBalkini, S. Khan, A. Harakeh, O. Andrienko, C. Reading, K. Czarnecki, and S. Waslander, "Unlimited Road-scene Synthetic Annotation (URSA) Dataset", The 21st IEEE International Conference on Intelligent Transportation Systems (ITSC), Maui, Hawaii, USA, IEEE, 11/2018. PDF icon 1807.06056.pdf (3.28 MB)
Chandail, R., "Vision Augmented State Estimation with Fault Tolerance", Electrical and Computer Engineering, vol. MASc, Waterloo, University of Waterloo, 05/2018.
2017
Zulkoski, E., C. Bright, A. Heinle, I. Kotsireas, K. Czarnecki, and V. Ganesh, "Combining SAT Solvers with Computer Algebra Systems to Verify Combinatorial Conjectures", Journal of Automated Reasoning, vol. 58, issue 3, pp. 339, 03/2011, 2017.
Guo, J., D. Yang, N. Siegmund, S. Apel, A. Sarkar, P. Valov, K. Czarnecki, A. Wąsowski, and H. Yu, Data-efficient performance learning for configurable systems, 2017.
Hartmanns, A., S. Sedwards, and P. D'Argenio, "Efficient Simulation-based Verification of Probabilistic Timed Automata", Winter Simulation Conference (WSC 2017), Las Vegas, USA, IEEE, pp. 1419–1430, 2017.
Zulkoski, E., R. Martins, C. Wintersteiger, R. Robere, J. Hui Liang, K. Czarnecki, and V. Ganesh, "Empirically Relating Complexity-theoretic Parameters with SAT Solver Performance", Pragmatics of Constraint Reasoning: EPIC, 08/2017.
Larsen, K. G., D. Peled, and S. Sedwards, "Memory-Efficient Tactics for Randomized LTL Model Checking", 9th Working Conference on Verified Software: Theories, Tools and Experiments (VSTTE 2017), vol. 10712, Heidelberg, Germany, Springer, pp. 152-169, 2017.
Chauchan, M., R. Pellizzoni, and K. Czarnecki, "Modeling the Effects of AUTOSAR Overheads on Application Timing and Schedulability", Design Automation Conference, 06/2017.
Queiroz, R., L. Passos, M. Tulio Valente, C. Hunsen, S. Apel, and K. Czarnecki, "The shape of feature code: an analysis of twenty C-preprocessor-based systems", Software & Systems Modeling, vol. 16, issue 1, pp. 96, 02/2017.
Kido, K., S. Sedwards, and I. Hasuo, "Switching Delays and the Skorokhod Distance in Incrementally Stable Switched Systems", 7th Workshop on Design, Modeling and Evaluation of Cyber Physical Systems (CyPhy 2017), vol. 11267, Seoul, South Korea, Springer, pp. 109–126, 2017.
Ross, J., A. Murashkin, J. Hui Liang, M. Antkiewicz, and K. Czarnecki, "Synthesis and Exploration of Multi-Level, Multi-Perspective Architectures of Automotive Embedded Systems", Software and Systems Modeling, 2017. Office presentation icon Jordan Ross seminar slides (long) (2.85 MB)Office presentation icon Jordan Ross MODELS'17 invited presentation slides (short) (1.59 MB)
Valov, P., J-C. Petkovich, J. Guo, S. Fischmeister, and K. Czarnecki, "Transferring Performance Prediction Models Across Different Hardware Platforms", International Conference on Performance Engineering, 04/2017.
Guo, J., E. Blais, K. Czarnecki, and P. van Beek, "A Worst-Case Analysis of Constraint-Based Algorithms for Exact Multi-objective Combinatorial Optimization", Canadian Conference on Artificial Intelligence, 05.2017.
2016
Liang, J. Hui, V. Ganesh, P. Poupart, and K. Czarnecki, "Exponential Recency Weighted Average Branching Heuristic for SAT Solvers", AAAI Conference on Artificial Intelligence, 02/2016.
Zulkoski, E., V. Ganesh, and K. Czarnecki, "MathCheck: A Math Assistant via a Combination of Computer Algebra Systems and SAT Solvers", International Joint Conference on Artificial Intelligence - Sister Conference Best Paper Track: AAAI Press, 07/2016.
Sarkar, A., "Meta-learning Performance Prediction of Highly Configurable Systems: A Cost-oriented Approach", David R. Cheriton School of Computer Science, vol. MMath, Waterloo, University of Waterloo, pp. 71, 04/2016.
Khalilov, E., J. Ross, M. Antkiewicz, M. Völter, and K. Czarnecki, "Modeling and Optimizing Automotive Electric/Electronic (E/E) Architectures: Towards Making Clafer Accessible to Practitioners", ISoLA 2016: Leveraging Applications of Formal Methods, Verification and Validation: Discussion, Dissemination, Applications, 10/2016.

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