21 citations · 31 across the 4 of their papers we have counts for
4 papers
Synergizing Physically Constrained MCMC and Chemical-Informed Gaussian Processes for Reaction Network Discovery
Runzhe Liu, Zihao Wang, Wenbo Yang +1
Extracting interpretable governing equations from sparse, noisy chemical time-series data remains difficult because discrete reaction topology and continuous kinetic parameters are…
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…
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…
Real-Time Machine-Learning-Based Optimization Using Input Convex Long Short-Term Memory Network
Zihao Wang, Donghan Yu, Zhe Wu
Neural network-based optimization and control methods, often referred to as black-box approaches, are increasingly gaining attention in energy and manufacturing systems, particular…