3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CE2026
Unsupervised Learning for AC Optimal Power Flow with Fast Physics-Aware Layer
Jiebao Zhang, Haoyu Yan, Zhichao Sheng +4
Learning to solve the Alternating Current Optimal Power Flow (AC-OPF) problem by neural networks (NNs) is a promising approach in real-time applications. Existing methods to ensure…
cs.LG2024
Understanding Representation of Deep Equilibrium Models from Neural Collapse Perspective
Haixiang Sun, Ye Shi
Deep Equilibrium Model (DEQ), which serves as a typical implicit neural network, emphasizes their memory efficiency and competitive performance compared to explicit neural networks…
cs.LG2022★ 3 cited
Alternating Differentiation for Optimization Layers
Haixiang Sun, Ye Shi, Jingya Wang +3
The idea of embedding optimization problems into deep neural networks as optimization layers to encode constraints and inductive priors has taken hold in recent years. Most existin…