Neural ODEs Meet Concurrent Learning: Stable Online Learning with Lyapunov Guarantees

arXiv:2609.32289 · eess.SY, cs.LG, cs.SY · Submitted 2026-09-26 · Read on arXiv

eess.SY, cs.LG, cs.SY

Submitted: 2026-09-26

Updated: 2026-09-26

Terminology

• Adam — 16× in this paper · explained in 2 episodes
• Adaptation — 16× in this paper · explained in 1 episode
• Ablation — 11× in this paper · explained in 1 episode
• Benchmark — 10× in this paper · explained in 2 episodes
• Error Decomposition — 5× in this paper · explained in 3 episodes
• Lyapunov function — 4× in this paper · explained in 2 episodes
• Generative AI — 3× in this paper · explained in 2 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• System Identification — 3× in this paper · explained in 3 episodes
• Core — 2× in this paper · explained in 2 episodes
• Regret — 2× in this paper · explained in 3 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adjoint Method — 1× in this paper · explained in 1 episode
• Adversarial Attacks — 1× in this paper · explained in 1 episode
• Gradient Flow — 1× in this paper · explained in 2 episodes
• Meta-learning — 1× in this paper · explained in 2 episodes
• Online Adaptation — 1× in this paper · explained in 3 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• System Identification and Control Using Lyapunov-Based Deep Neural Networks without Persistent Excitation: A Concurrent Learning Approach
• DeepMind Control Suite

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