25 citations · 25 across the 3 of their papers we have counts for
6 papers
Convergent Proximal Multiblock ADMM for Nonconvex Dynamics-Constrained Optimization
Bowen Li, Ya-xiang Yuan
This paper proposes a provably convergent multiblock ADMM for nonconvex optimization with nonlinear dynamics constraints, overcoming the divergence issue in classical extensions. W…
Gradient Alignment in Physics-informed Neural Networks: A Second-Order Optimization Perspective
Sifan Wang, Ananyae Kumar Bhartari, Bowen Li +1
Multi-task learning through composite loss functions is fundamental to modern deep learning, yet optimizing competing objectives remains challenging. We present new theoretical and…
Numerical Solution for Nonlinear 4D Variational Data Assimilation (4D-Var) via ADMM
Bowen Li, Bin Shi
The four-dimensional variational data assimilation (4D-Var) has emerged as an important methodology, widely used in numerical weather prediction, oceanographic modeling, and climat…
Understanding the PDHG Algorithm via High-Resolution Differential Equations
Bowen Li, Bin Shi
The least absolute shrinkage and selection operator (Lasso) is widely recognized across various fields of mathematics and engineering. Its variant, the generalized Lasso, finds ext…
PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks
Sifan Wang, Bowen Li, Yuhan Chen +1
While physics-informed neural networks (PINNs) have become a popular deep learning framework for tackling forward and inverse problems governed by partial differential equations (P…
Understanding the ADMM Algorithm via High-Resolution Differential Equations
Bowen Li, Bin Shi
In the fields of statistics, machine learning, image science, and related areas, there is an increasing demand for decentralized collection or storage of large-scale datasets, as w…