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https://github.com/hemumanju/lead-literature


https://github.com/hemumanju/lead-literature

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# Literature on Learning Enabled Assistive Driving

## Learning

1. Leung, Karen, Nikos Aréchiga, and Marco Pavone. ["Back-propagation through signal temporal logic specifications: Infusing logical structure into gradient-based methods."](https://arxiv.org/pdf/2008.00097) In International Workshop on the Algorithmic Foundations of Robotics, pp. 432-449. Springer, Cham, 2021.
2. Pak, Andrey, Hemanth Manjunatha, Dimitar Filev, and Panagiotis Tsiotras. ["CARNet: A Dynamic Autoencoder for Learning Latent Dynamics in Autonomous Driving Tasks."](https://arxiv.org/pdf/2205.08712) arXiv preprint arXiv:2205.08712 (2022).
3. Manjunatha, Hemanth, Andrey Pak, Dimitar Filev, and Panagiotis Tsiotras. ["Karnet: Kalman filter augmented recurrent neural network for learning world models in autonomous driving tasks."](https://arxiv.org/abs/2305.14644) arXiv preprint arXiv:2305.14644 (2023).
4. Manjunatha, Hemanth, and Panagiotis Tsiotras. ["Beyond One Model Fits All: Ensemble Deep Learning for Autonomous Vehicles."](https://arxiv.org/abs/2312.05759) arXiv preprint arXiv:2312.05759 (2023).

## Inverse Reinforcement Learning

## Runtime Assurance

1. Hobbs, Kerianne, Mark Mote, Matthew Abate, Samuel Coogan, and Eric Feron. ["Run time assurance for safety-critical systems: An introduction to safety filtering approaches for complex control systems."](https://arxiv.org/pdf/2110.03506) arXiv preprint arXiv:2110.03506 (2021).
2. Saber Jafarpour, Akash Harapanahalli, Samuel Coogan. ["Interval Reachability of Nonlinear Dynamical Systems with Neural Network Controllers."](https://github.com/gtfactslab/L4DC2023_NNControllerReachability/blob/main/Final_Manuscript_with_Proofs/2022_NNController.pdf)
3. Coogan, Samuel. ["Mixed monotonicity for reachability and safety in dynamical systems."](https://par.nsf.gov/servlets/purl/10210423) In 2020 59th IEEE Conference on Decision and Control (CDC), pp. 5074-5085. IEEE, 2020.