Shancong Mou — accepted AI-conference papers

2026

Natural Hypergradient Descent: Algorithm Design, Convergence Analysis, and Parallel Implementation

Deyi Kong, Zaiwei Chen, Shuzhong Zhang, Shancong Mou

ICML 2026poster

In this work, we propose *Natural Hypergradient Descent* (NHGD), a new method for solving bilevel optimization problems. To address the computational bottleneck in hypergradient estimation—namely, the need to compute or approximate Hessian inverses—we exploit the statistical structure of the inner o…

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2023

RGI: robust GAN-inversion for mask-free image inpainting and unsupervised pixel-wise anomaly detection

Shancong Mou, Xiaoyi Gu, Meng Cao, Haoping Bai, Ping Huang, Jiulong Shan +1

ICLR 2023poster

Generative adversarial networks (GANs), trained on a large-scale image dataset, can be a good approximator of the natural image manifold. GAN-inversion, using a pre-trained generator as a deep generative prior, is a promising tool for image restoration under corruptions. However, the performance of…

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