Exploiting Spiking Dynamics with Spatial-temporal Feature Normalization in Graph Learning

no code implementations • 30 Jun 2021 • Mingkun Xu, Yujie Wu, Lei Deng, Faqiang Liu, Guoqi Li, Jing Pei

Biological spiking neurons with intrinsic dynamics underlie the powerful representation and learning capabilities of the brain for processing multimodal information in complex environments.

Graph Attention Graph Learning +1

Towards Both Accurate and Robust Neural Networks without Extra Data

1 code implementation • 24 Mar 2021 • Faqiang Liu, Rong Zhao

The AFS model achieves a benign accuracy improvement of ~6% on CIFAR-10 and ~10% on CIFAR-100 with comparable or even stronger robustness than the state-of-the-art adversarial training methods.

Adversarial symmetric GANs: bridging adversarial samples and adversarial networks

1 code implementation • 20 Dec 2019 • Faqiang Liu, Mingkun Xu, Guoqi Li, Jing Pei, Luping Shi, Rong Zhao

Generative adversarial networks have achieved remarkable performance on various tasks but suffer from training instability.

Image Generation

BRIDGING ADVERSARIAL SAMPLES AND ADVERSARIAL NETWORKS

no code implementations • 25 Sep 2019 • Faqiang Liu, Mingkun Xu, Guoqi Li, Jing Pei, Luping Shi

Generative adversarial networks have achieved remarkable performance on various tasks but suffer from sensitivity to hyper-parameters, training instability, and mode collapse.

Image Generation