3 papers indexed
Zhongchen Zhao, Jixin Wang, Qi Xie, Hui Lin, Lei Zhang, Deyu Meng, et al.
Equivariant networks embed geometric symmetries as structural priors through weight sharing, achieving remarkable parameter efficiency across vision tasks. However, this parameter efficiency does not translate into compute efficiency: existing implementations unroll the structure…
Yubo Zhou, Jun Shu, Luo Luo, Junmin Liu, Deyu Meng, Guang Dai, et al.
Bilevel optimization underpins many machine learning applications, including hyperparameter optimization, meta-learning, neural architecture search, and reinforcement learning. While hypergradient-based methods have advanced significantly, a gap persists between theoretical guara…
Zirui Deng, Jingbo Sun, Deyu Meng, Fei Wang
Repeatedly solving parametric PDEs is essential for uncertainty quantification, design optimization and inverse problems, but conventional neural operators require expensive non-convex training. We introduce PCA--RaNN, a randomized latent neural operator that combines PCA-based d…