2 papers
eess.SY2025
Mixed Monotonicity Reachability Analysis of Neural ODE: A Trade-Off Between Tightness and Efficiency
Abdelrahman Sayed Sayed, Pierre-Jean Meyer, Mohamed Ghazel
Neural ordinary differential equations (neural ODE) are powerful continuous-time machine learning models for depicting the behavior of complex dynamical systems, but their verifica…
cs.LG2025
Bridging Neural ODE and ResNet: A Formal Error Bound for Safety Verification
Abdelrahman Sayed Sayed, Pierre-Jean Meyer, Mohamed Ghazel
A neural ordinary differential equation (neural ODE) is a machine learning model that is commonly described as a continuous-depth generalization of a residual network (ResNet) with…