Anton Tsitsulin | DeepAI

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∙ 07/26/2023

HUGE: Huge Unsupervised Graph Embeddings with TPUs

Graphs are a representation of structured data that captures the relatio...

0 Brandon Mayer, et al. ∙

∙ 07/17/2023

Examining the Effects of Degree Distribution and Homophily in Graph Learning Models

Despite a surge in interest in GNN development, homogeneity in benchmark...

0 Mustafa Yasir, et al. ∙

∙ 05/26/2023

Unsupervised Embedding Quality Evaluation

Unsupervised learning has recently significantly gained in popularity, e...

0 Anton Tsitsulin, et al. ∙

∙ 07/14/2022

Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank

Personalized PageRank (PPR) is a fundamental tool in unsupervised learni...

0 Alessandro Epasto, et al. ∙

∙ 05/20/2022

Tackling Provably Hard Representative Selection via Graph Neural Networks

Representative selection (RS) is the problem of finding a small subset o...

0 Seyed Mehran Kazemi, et al. ∙

∙ 04/04/2022

Synthetic Graph Generation to Benchmark Graph Learning

Graph learning algorithms have attained state-of-the-art performance on ...

0 Anton Tsitsulin, et al. ∙

∙ 02/28/2022

GraphWorld: Fake Graphs Bring Real Insights for GNNs

Despite advances in the field of Graph Neural Networks (GNNs), only a sm...

0 John Palowitch, et al. ∙

∙ 06/10/2021

GRASP: Graph Alignment through Spectral Signatures

What is the best way to match the nodes of two graphs? This graph alignm...

0 Judith Hermanns, et al. ∙

∙ 10/14/2020

InstantEmbedding: Efficient Local Node Representations

In this paper, we introduce InstantEmbedding, an efficient method for ge...

25 Ştefan Postăvaru, et al. ∙

∙ 06/30/2020

Graph Clustering with Graph Neural Networks

Graph Neural Networks (GNNs) have achieved state-of-the-art results on m...

0 Anton Tsitsulin, et al. ∙

∙ 06/08/2020

FREDE: Linear-Space Anytime Graph Embeddings

Low-dimensional representations, or embeddings, of a graph's nodes facil...

6 Anton Tsitsulin, et al. ∙

∙ 03/03/2020

Just SLaQ When You Approximate: Accurate Spectral Distances for Web-Scale Graphs

Graph comparison is a fundamental operation in data mining and informati...

0 Anton Tsitsulin, et al. ∙

∙ 05/27/2019

Intrinsic Multi-scale Evaluation of Generative Models

Generative models are often used to sample high-dimensional data points ...

5 Anton Tsitsulin, et al. ∙

∙ 11/15/2018

SGR: Self-Supervised Spectral Graph Representation Learning

Representing a graph as a vector is a challenging task; ideally, the rep...

0 Anton Tsitsulin, et al. ∙

∙ 03/13/2018

VERSE: Versatile Graph Embeddings from Similarity Measures

Embedding a web-scale information network into a low-dimensional vector ...

0 Anton Tsitsulin, et al. ∙

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