ETD

• continual learning
• dynamical systems
• incremental learning
• physical systems
• physics informed neural network
• physics-informed learning
• PINN
• scientific machine learning
• SciML

The thesis addresses the problem of learning physical systems in a continual learning environment (Continual Physics-Informed Learning), leveraging physics-informed neural network models, continual learning methods, and derivative distillation.