activity
20192023
most citedTackling Catastrophic Forgetting and Background Shift in Continual Semantic Segmentation

11 citations · 20 across the 7 of their papers we have counts for

collaborators

8 papers

cs.LG2023★ 3 cited

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…

eess.SY2022

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…

cs.CV2021★ 11 cited

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.…

cs.CV2020

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.…

cs.CL2019★ 2 cited

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…

cs.LG2019

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…