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Debarghya Ghoshdastidar — most-cited papers & profile · Graph Learning
← authors
·
overview
Debarghya Ghoshdastidar
10
papers ·
0
citations ·
11
h-index
Tumaini University · Tumkur University · Technical University of Munich
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Most-cited papers
Different Statistical Perspectives for Understanding Generalisation in Graph Neural Networks
2026
Gaussian Process Limit Reveals Structural Benefits of Graph Transformers
2026
Exact Generalisation Error Exposes Benchmarks Skew Graph Neural Networks Success (or Failure)
2025
Two-Sample Tests for Large Random Graphs Using Network Statistics
2017
Two-sample Hypothesis Testing for Inhomogeneous Random Graphs
2017
Practical methods for graph two-sample testing
2018
Graphon based Clustering and Testing of Networks: Algorithms and Theory
2021
New Insights into Graph Convolutional Networks using Neural Tangent Kernels
2021
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks
2021
A Revenue Function for Comparison-Based Hierarchical Clustering
2022
Top co-authors
Mahalakshmi Sabanayagam
· 4
Nil Ayday
· 3
Ulrike von Luxburg
· 3
Alexandra Carpentier
· 2
Leena Chennuru Vankadara
· 2
Maurilio Gutzeit
· 2
Aishik Mandal
· 1
Lingchu Yang
· 1
Micha\"el Perrot
· 1
Pascal Esser
· 1
Pascal Mattia Esser
· 1
Topics
cs.LG
stat.ML
Uncategorized
stat.ME