MP4b.2

A Simplified Framework for Contrastive Learning for Node Representations

Ilgee Hong, Huy Tran, Claire Donnat, The University of Chicago, United States
Session:
MP4b: Graph Signal Processing Lecture
Track:
Networks
Location:
Nautilus
Presentation Time:
Mon, 30 Oct, 15:55 - 16:20 PT (UTC -8)
Session Chair:
John Shi, Carnegie Mellon University
Presentation
Discussion
Resources
No resources available.
Session MP4b
MP4b.1: Convergence of Graph Neural Networks on Relatively Sparse Graphs
Zhiyang Wang, University of Pennsylvania, United States; Luana Ruiz, Johns Hopkins University, United States; Alejandro Ribeiro, University of Pennsylvania, United States
MP4b.2: A Simplified Framework for Contrastive Learning for Node Representations
Ilgee Hong, Huy Tran, Claire Donnat, The University of Chicago, United States
MP4b.3: Robust Graph Neural Network Based on Graph Denoising
Victor M. Tenorio, Samuel Rey, Antonio G. Marques, King Juan Carlos University, Spain
MP4b.4: Graph Classification via Simple Graph Based Features
Farida Abdelmoneum, John Shi, Jose M. F. Moura, Carnegie Mellon University, United States
MP4b.5: A Belief Propagation Approach for Direct Multipath-Based SLAM
Mingchao Liang, University of California, San Diego, United States; Erik Leitinger, Graz University of Technology, Austria; Florian Meyer, University of California, San Diego, United States
Contacts