“…based on Gaussian processes (Deisenroth et al, 2015;Kabzan et al, 2019) or neural networks (Raissi et al, 2018;Chua et al, 2018). For physical systems, recent works (Lutter et al, 2019;Zhong et al, 2019;Duong and Atanasov, 2021b) design the model architecture to encode Lagrangian or Hamiltonian formulation of robot dynamics (Lurie, 2013;Holm, 2008), which a black-box model might struggle to infer. For Hamiltonian formulation, Zhong et al (2019) use a differentiable neural ODE solver (Chen et al, 2018) to generate predicted state trajectory.…”