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David Wipf — most-cited papers & profile · Graph Learning
← authors
·
overview
David Wipf
21
papers ·
384
citations ·
38
h-index
Amazon (United States)
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification
2023 · 75 citations
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks
2021 · 49 citations
Learning Hierarchical Graph Neural Networks for Image Clustering
2021 · 36 citations
Bag of Tricks for Node Classification with Graph Neural Networks
2021 · 28 citations
Graph Neural Networks Inspired by Classical Iterative Algorithms
2021 · 13 citations
Network In Graph Neural Network
2021 · 7 citations
Refined Edge Usage of Graph Neural Networks for Edge Prediction
2022 · 1 citations
Implicit vs Unfolded Graph Neural Networks
2021
From Hypergraph Energy Functions to Hypergraph Neural Networks
2023
How Graph Neural Networks Learn: Lessons from Training Dynamics
2023
Efficient Link Prediction via GNN Layers Induced by Negative Sampling
2023
MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy
2023
Top co-authors
Yangkun Wang
· 4
Zheng Zhang
· 4
Junchi Yan
· 3
Qitian Wu
· 3
Zengfeng Huang
· 3
Jiarui Jin
· 2
Tang Liu
· 2
Weinan Zhang
· 2
Xiang Song
· 2
Xipeng Qiu
· 2
Xuanjing Huang
· 2
Yongyi Yang
· 2
Topics
GNN Architectures
Theory & Expressivity
Self-Supervised & Contrastive
Scene & Visual Graphs
Recommendation Graphs