11 citations · 20 across the 7 of their papers we have counts for
8 papers
Hybrid Augmented Automated Graph Contrastive Learning
Yifu Chen, Qianqian Ren, Liu Yong
Graph augmentations are essential for graph contrastive learning. Most existing works use pre-defined random augmentations, which are usually unable to adapt to different input gra…
Deep Learning-based Predictive Control of Battery Management for Frequency Regulation
Yun Li, Yixiu Wang, Yifu Chen +5
This paper proposes a deep learning-based optimal battery management scheme for frequency regulation (FR) by integrating model predictive control (MPC), supervised learning (SL), r…
Tackling Catastrophic Forgetting and Background Shift in Continual Semantic Segmentation
Arthur Douillard, Yifu Chen, Arnaud Dapogny +1
Deep learning approaches are nowadays ubiquitously used to tackle computer vision tasks such as semantic segmentation, requiring large datasets and substantial computational power.…
PLOP: Learning without Forgetting for Continual Semantic Segmentation
Arthur Douillard, Yifu Chen, Arnaud Dapogny +1
Deep learning approaches are nowadays ubiquitously used to tackle computer vision tasks such as semantic segmentation, requiring large datasets and substantial computational power.…
Guiding Variational Response Generator to Exploit Persona
Bowen Wu, Mengyuan Li, Zongsheng Wang +5
Leveraging persona information of users in Neural Response Generators (NRG) to perform personalized conversations has been considered as an attractive and important topic in the re…
REVE: Regularizing Deep Learning with Variational Entropy Bound
Antoine Saporta, Yifu Chen, Michael Blot +1
Studies on generalization performance of machine learning algorithms under the scope of information theory suggest that compressed representations can guarantee good generalization…
MemeFaceGenerator: Adversarial Synthesis of Chinese Meme-face from Natural Sentences
Yifu Chen, Zongsheng Wang, Bowen Wu +6
Chinese meme-face is a special kind of internet subculture widely spread in Chinese Social Community Networks. It usually consists of a template image modified by some amusing deta…
SEMEDA: Enhancing Segmentation Precision with Semantic Edge Aware Loss
Yifu Chen, Arnaud Dapogny, Matthieu Cord
While nowadays deep neural networks achieve impressive performances on semantic segmentation tasks, they are usually trained by optimizing pixel-wise losses such as cross-entropy.…