8 citations · 12 across the 3 of their papers we have counts for
3 papers
cs.CV2023
Layer-adaptive Structured Pruning Guided by Latency
Siyuan Pan, Linna Zhang, Jie Zhang +3
Structured pruning can simplify network architecture and improve inference speed. Combined with the underlying hardware and inference engine in which the final model is deployed, b…
cs.LG2022★ 4 cited
Augmentation-Aware Self-Supervision for Data-Efficient GAN Training
Liang Hou, Qi Cao, Yige Yuan +7
Training generative adversarial networks (GANs) with limited data is challenging because the discriminator is prone to overfitting. Previously proposed differentiable augmentation…
cs.LG2021★ 8 cited
Conditional GANs with Auxiliary Discriminative Classifier
Liang Hou, Qi Cao, Huawei Shen +3
Conditional generative models aim to learn the underlying joint distribution of data and labels to achieve conditional data generation. Among them, the auxiliary classifier generat…