| 2025 | ICLR | Neural Stochastic Differential Equations for Uncertainty-Aware Offline RL. | Cevahir Kprl, Franck Djeumou, Ufuk Topcu |
| 2025 | ICRA | Reference-Free Formula Drift with Reinforcement Learning: From Driving Data to Tire Energy-Inspired, Real-World Policies. | Franck Djeumou, Michael Thompson, Makoto Suminaka, John K. Subosits |
| 2025 | ICRA | Risk-Averse Model Predictive Control for Racing in Adverse Conditions. | Thomas Lew, Marcus Greiff, Franck Djeumou, Makoto Suminaka, Michael Thompson, John K. Subosits |
| 2024 | CoRL | One Model to Drift Them All: Physics-Informed Conditional Diffusion Model for Driving at the Limits. | Franck Djeumou, Thomas Lew, Nan Ding, Michael Thompson, Makoto Suminaka, Marcus Greiff, John K. Subosits |
| 2023 | CoRL | How to Learn and Generalize From Three Minutes of Data: Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential Equations. | Franck Djeumou, Cyrus Neary, Ufuk Topcu |
| 2023 | ICRA | Autonomous Drifting with 3 Minutes of Data via Learned Tire Models. | Franck Djeumou, Jonathan Y. M. Goh, Ufuk Topcu, Avinash Balachandran |
| 2022 | IJCAI | Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEs. | Franck Djeumou, Cyrus Neary, Eric Goubault, Sylvie Putot, Ufuk Topcu |