21 citations · 31 across the 4 of their papers we have counts for
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cs.LG2026
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…
cs.LG2024★ 1 cited
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.LG2023★ 21 cited
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…