Neural networks with physics-informed architectures and constraints for dynamical systems modeling F Djeumou, C Neary, E Goubault, S Putot, U Topcu Learning for Dynamics and Control Conference, 263-277, 2022 | 91 | 2022 |
Probabilistic Swarm Guidance Subject to Graph Temporal Logic Specifications. F Djeumou, Z Xu, U Topcu Robotics: Science and Systems, 2020 | 23 | 2020 |
On-the-fly control of unknown smooth systems from limited data F Djeumou, AP Vinod, E Goubault, S Putot, U Topcu 2021 American Control Conference (ACC), 3656-3663, 2021 | 21 | 2021 |
Autonomous drifting with 3 minutes of data via learned tire models F Djeumou, JYM Goh, U Topcu, A Balachandran 2023 IEEE International Conference on Robotics and Automation (ICRA), 968-974, 2023 | 19 | 2023 |
Taylor-lagrange neural ordinary differential equations: Toward fast training and evaluation of neural odes F Djeumou, C Neary, E Goubault, S Putot, U Topcu arXiv preprint arXiv:2201.05715, 2022 | 17 | 2022 |
On-the-fly control of unknown systems: From side information to performance guarantees through reachability F Djeumou, AP Vinod, E Goubault, S Putot, U Topcu IEEE Transactions on Automatic Control 68 (8), 4857-4872, 2022 | 14 | 2022 |
Physics-informed kernel embeddings: Integrating prior system knowledge with data-driven control AJ Thorpe, C Neary, F Djeumou, MMK Oishi, U Topcu 2024 American Control Conference (ACC), 3130-3137, 2024 | 11 | 2024 |
How to learn and generalize from three minutes of data: Physics-constrained and uncertainty-aware neural stochastic differential equations F Djeumou, C Neary, U Topcu arXiv preprint arXiv:2306.06335, 2023 | 10 | 2023 |
Probabilistic control of heterogeneous swarms subject to graph temporal logic specifications: A decentralized and scalable approach F Djeumou, Z Xu, M Cubuktepe, U Topcu IEEE Transactions on Automatic Control 68 (4), 2245-2260, 2022 | 10 | 2022 |
Online synthesis for runtime enforcement of safety in multiagent systems D Raju, S Bharadwaj, F Djeumou, U Topcu IEEE Transactions on Control of Network Systems 8 (2), 621-632, 2021 | 10 | 2021 |
Learning to reach, swim, walk and fly in one trial: Data-driven control with scarce data and side information F Djeumou, U Topcu Learning for Dynamics and Control Conference, 453-466, 2022 | 7 | 2022 |
On-the-fly, data-driven reachability analysis and control of unknown systems: an F-16 aircraft case study F Djeumou, A Zutshi, U Topcu Proceedings of the 24th International Conference on Hybrid Systems …, 2021 | 6 | 2021 |
Task-guided inverse reinforcement learning under partial information F Djeumou, M Cubuktepe, C Lennon, U Topcu Proceedings of the international conference on automated planning and …, 2022 | 5 | 2022 |
Policy synthesis for switched linear systems with Markov decision process switching B Wu, M Cubuktepe, F Djeumou, Z Xu, U Topcu IEEE Transactions on Automatic Control 68 (1), 532-539, 2022 | 5 | 2022 |
Learning-based, safety-constrained control from scarce data via reciprocal barriers CK Verginis, F Djeumou, U Topcu 2021 60th IEEE Conference on Decision and Control (CDC), 83-89, 2021 | 4 | 2021 |
Safety-constrained learning and control using scarce data and reciprocal barriers CK Verginis, F Djeumou, U Topcu arXiv preprint arXiv:2105.06526, 2021 | 4 | 2021 |
One model to drift them all: Physics-informed conditional diffusion model for driving at the limits F Djeumou, TJ Lew, N Ding, M Thompson, M Suminaka, M Greiff, ... 8th Annual Conference on Robot Learning, 2024 | 3 | 2024 |
Blending controllers via multi-objective bandits P Gohari, F Djeumou, AP Vinod, U Topcu 2022 American Control Conference (ACC), 88-95, 2022 | 2 | 2022 |
Learning to Reach, Swim, Walk and Fly in One Trial: Data-Driven Control with Scarce Data and Side Information F Djeumou, U Topcu arXiv preprint arXiv:2106.10533, 2021 | 1 | 2021 |
First, Learn What You Don't Know: Active Information Gathering for Driving at the Limits of Handling A Davydov, F Djeumou, M Greiff, M Suminaka, M Thompson, J Subosits, ... arXiv preprint arXiv:2411.00107, 2024 | | 2024 |