2 papers
cs.LG2026
Input Convex Lipschitz Recurrent Neural Networks for Robust and Efficient Process Modeling and Optimization
Zihao Wang, Yuhan Li, Yao Shi +1
Computational efficiency and robustness are essential in process modeling, optimization, and control for real-world engineering applications. While neural network-based approaches…
cs.CE2025
Towards Foundation Model for Chemical Reactor Modeling: Meta-Learning with Physics-Informed Adaptation
Zihao Wang, Zhe Wu
Developing accurate models for chemical reactors is often challenging due to the complexity of reaction kinetics and process dynamics. Traditional approaches require retraining mod…