activity
20172022
most citedAdversarial Graph Augmentation to Improve Graph Contrastive Learning

142 citations · 504 across the 29 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.LG20222 cited

Federated Graph Representation Learning using Self-Supervision

Susheel Suresh, Danny Godbout, Arko Mukherjee +3

Federated graph representation learning (FedGRL) brings the benefits of distributed training to graph structured data while simultaneously addressing some privacy and compliance co…

cs.AI20221 cited

A Novel Membership Inference Attack against Dynamic Neural Networks by Utilizing Policy Networks Information

Pan Li, Peizhuo Lv, Shenchen Zhu +2

Unlike traditional static deep neural networks (DNNs), dynamic neural networks (NNs) adjust their structures or parameters to different inputs to guarantee accuracy and computation…

cs.CV20221 cited

Spatio-temporal Tendency Reasoning for Human Body Pose and Shape Estimation from Videos

Boyang Zhang, SuPing Wu, Hu Cao +3

In this paper, we present a spatio-temporal tendency reasoning (STR) network for recovering human body pose and shape from videos. Previous approaches have focused on how to extend…

cs.CR20221 cited

Robust Fingerprinting of Genomic Databases

Tianxi Ji, Erman Ayday, Emre Yilmaz +1

Database fingerprinting has been widely used to discourage unauthorized redistribution of data by providing means to identify the source of data leakages. However, there is no fing…

cs.LG202223 cited

Graph Auto-Encoder Via Neighborhood Wasserstein Reconstruction

Mingyue Tang, Carl Yang, Pan Li

Graph neural networks (GNNs) have drawn significant research attention recently, mostly under the setting of semi-supervised learning. When task-agnostic representations are prefer…