Publications

 Here is a list of our publications related to the TensorCell research:  

1. Gora P., Bogucki D., Bolum L.M., "Explainability of Surrogate Models for Traffic Signal Control", in "Explainable Artificial Intelligence for Intelligent Transportation Systems", 1st Edition, CRC Press, 2023.

2. Skowronek Ł., Gora P., Możejko M., Klemenko A. (2023). "Graph-Based Sparse Neural Networks for Traffic Signal Optimization". In: Schlingloff, BH., Vogel, T., Skowron, A. (eds) "Concurrency, Specification and Programming. Studies in Computational Intelligence", vol 1091. Springer, Cham. https://doi.org/10.1007/978-3-031-26651-5_9.

3. Skowronek Ł., Gora P., Możejko M., Klemenko A., "Graph-based Sparse Neural Networks for Traffic Signal Optimization", Proceedings of the 29th International Workshop on Concurrency, Specification and Programming (CS&P 2021), 2021. 

4. Szejgis W., Warno A., Gora P., "Predicting times of waiting on red signals using BERT", in NeurIPS 2020 Workshop on Machine Learning for Autonomous Driving.

5. Borowski M., Gora P., Karnas K., Błajda M., Król K., Matyjasek A., Burczyk D., Szewczyk M., and Kutwin M., "New Hybrid Quantum Annealing Algorithms for Solving Vehicle Routing Problem", Computational Science - ICCS 2020, 2020, pp. 546-561.

6. Gora P., Bankiewicz D., Karnas K., Kaźmierczak W., Kutwin M., Perkowski P., Płotka S., Szczurek A., Zięba D., "On a road to optimal fleet routing algorithms: a gentle introduction to the state-of-the-art", in "Solving Complex Vehicle Routing Problems. Intelligent Data-Centric Systems", 2020, pp. 37-92.

7. Gora P. et al., "Solving Traffic Signal Setting Problem Using Machine Learning", 2019 6th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), Cracow, Poland, 2019, pp. 1-10.

8. Możejko M., Brzeski M., Mądry Ł., Skowronek Ł., Gora P., "Traffic Signal Settings Optimization Using Gradient Descent", in "Schedae Informaticae", Vol. 27, 2018, pp. 19–30.

9. Gora P., Możejko M., Brzeski M., Klemenko A., Kochański A., "Investigating performance of neural networks and gradient boosting models approximating microscopic traffic simulations in traffic optimization tasks", presented at NeurIPS 2018 Workshop "Machine Learning for Intelligent Transportation Systems".

10. Gora P., Bardoński M., "Training neural networks to approximate traffic simulation outcomes", in "2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), IEEE", pp. 889–894.

11. Gora P., Kurach K. "Approximating Traffic Simulation using Neural Networks and its Application in Traffic Optimization", in "NIPS 2016 Workshop on Nonconvex Optimization for Machine Learning: Theory and Practice".

12. Gora P., Pardel P., "Application of genetic algorithms and high-performance computing to the Traffic Signal Setting problem", in "24th International Workshop, CS&P 2015, Vol. 1", Rzeszów, 2015, pp. 146-157.

13. Gora P., "A genetic algorithm approach to optimization of vehicular traffic in cities by means of configuring traffic lights", in "Emergent Intelligent Technologies in the Industry", 2011, pp. 1-10.

14. Gora P., "Adaptive planning of vehicular traffic", M.Sc. thesis in Computer Science, 2010.

15. Gora P., "Traffic Simulation Framework - a Cellular Automaton based tool for simulating and investigating real city traffic", in "Recent Advances in Intelligent Information Systems", 2009, pp. 641-653, ISBN: 978-83-60434-59-8.