Learning Robust State Observers using Neural ODEs (longer version). - Keyan Miao; Konstantinos Gatsis (CoRR, 2022)

Learning Robust State Observers using Neural ODEs. - Keyan Miao; Konstantinos Gatsis (L4DC, 2023)

How Deep Do We Need: Accelerating Training and Inference of Neural ODEs via Control Perspective. - Keyan Miao; Konstantinos Gatsis (ICML, 2024)

NLBAC: A Neural Ordinary Differential Equations-based Framework for Stable and Safe Reinforcement Learning. - Liqun Zhao; Keyan Miao; Konstantinos Gatsis; Antonis Papachristodoulou (CoRR, 2024)

Opt-ODENet: Neural ODE Controller Design with Differentiable Optimization Layers for Safety and Stability. - Keyan Miao; Liqun Zhao; Han Wang 026; Konstantinos Gatsis; Antonis Papachristodoulou (L4DC, 2025)

NLBAC: A neural ODE-based algorithm for state-wise stable and safe reinforcement learning. - Liqun Zhao; Keyan Miao; Hongpeng Cao; Konstantinos Gatsis; Antonis Papachristodoulou (Neurocomputing, 2025)

Opt-ODENet: A Neural ODE Framework with Differentiable QP Layers for Safe and Stable Control Design (longer version). - Keyan Miao; Liqun Zhao; Han Wang 026; Konstantinos Gatsis; Antonis Papachristodoulou (CoRR, 2025)

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity. - Han Wang 026; Keyan Miao; Diego de S. Madeira; Antonis Papachristodoulou (CoRR, 2025)