Anton Tsitsulin

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 43

Top Topics

Spectral Signatures

Quality Evaluation

Structured Data

Temporal Reasoning

Top Venues

Proc. VLDB Endow.

Publications

Clayton Sanford, Bahare Fatemi, Ethan Hall, Anton Tsitsulin, Seyed Mehran Kazemi, Jonathan Halcrow, Bryan Perozzi, Vahab Mirrokni
Understanding Transformer Reasoning Capabilities via Graph Algorithms. CoRR (2024)
Bahare Fatemi, Mehran Kazemi, Anton Tsitsulin, Karishma Malkan, Jinyeong Yim, John Palowitch, Sungyong Seo, Jonathan Halcrow, Bryan Perozzi
Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning. CoRR (2024)
Bryan Perozzi, Bahare Fatemi, Dustin Zelle, Anton Tsitsulin, Seyed Mehran Kazemi, Rami Al-Rfou, Jonathan Halcrow
Let Your Graph Do the Talking: Encoding Structured Data for LLMs. CoRR (2024)
Anton Tsitsulin, Bryan Perozzi, Bahare Fatemi, Jonathan J. Halcrow
Graph Reasoning with LLMs (GReaL). KDD (2024)
Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights. CoRR (2024)
Jialin Dong, Bahare Fatemi, Bryan Perozzi, Lin F. Yang, Anton Tsitsulin
Don't Forget to Connect! Improving RAG with Graph-based Reranking. CoRR (2024)
Judith Hermanns, Konstantinos Skitsas, Anton Tsitsulin, Marina Munkhoeva, Alexander Frederiksen Kyster, Simon Nielsen, Alexander M. Bronstein, Davide Mottin, Panagiotis Karras
GRASP: Scalable Graph Alignment by Spectral Corresponding Functions. ACM Trans. Knowl. Discov. Data 17 (4) (2023)
Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi
Unsupervised Embedding Quality Evaluation. CoRR (2023)
Bahare Fatemi, Sami Abu-El-Haija, Anton Tsitsulin, Seyed Mehran Kazemi, Dustin Zelle, Neslihan Bulut, Jonathan Halcrow, Bryan Perozzi
UGSL: A Unified Framework for Benchmarking Graph Structure Learning. CoRR (2023)
Brandon A. Mayer, Anton Tsitsulin, Hendrik Fichtenberger, Jonathan Halcrow, Bryan Perozzi
HUGE: Huge Unsupervised Graph Embeddings with TPUs. KDD (2023)
Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller
Graph Clustering with Graph Neural Networks. J. Mach. Learn. Res. 24 (2023)
Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi
Unsupervised Embedding Quality Evaluation. TAG-ML (2023)
Anton Tsitsulin, Bryan Perozzi
The Graph Lottery Ticket Hypothesis: Finding Sparse, Informative Graph Structure. CoRR (2023)
Bryan Perozzi, Sami Abu-El-Haija, Anton Tsitsulin
Graph Neural Networks in TensorFlow. KDD (2023)
Mustafa Yasir, John Palowitch, Anton Tsitsulin, Long Tran-Thanh, Bryan Perozzi
Examining the Effects of Degree Distribution and Homophily in Graph Learning Models. CoRR (2023)
Jiaqi Ma, Jiong Zhu, Yuxiao Dong, Danai Koutra, Jingrui He, Qiaozhu Mei, Anton Tsitsulin, Xingjian Zhang, Marinka Zitnik
The 3rd Workshop on Graph Learning Benchmarks (GLB 2023). KDD (2023)
Brandon A. Mayer, Anton Tsitsulin, Hendrik Fichtenberger, Jonathan Halcrow, Bryan Perozzi
HUGE: Huge Unsupervised Graph Embeddings with TPUs. CoRR (2023)
Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, MohammadHossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab Mirrokni
Tackling Provably Hard Representative Selection via Graph Neural Networks. Trans. Mach. Learn. Res. 2023 (2023)
Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. CoRR (2022)
Seyed Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, MohammadHossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab S. Mirrokni
Tackling Provably Hard Representative Selection via Graph Neural Networks. CoRR (2022)
Anton Tsitsulin, Benedek Rozemberczki, John Palowitch, Bryan Perozzi
Synthetic Graph Generation to Benchmark Graph Learning. CoRR (2022)
Kimon Fountoulakis, Dake He, Silvio Lattanzi, Bryan Perozzi, Anton Tsitsulin, Shenghao Yang
On Classification Thresholds for Graph Attention with Edge Features. CoRR (2022)
John Palowitch, Anton Tsitsulin, Brandon Mayer, Bryan Perozzi
GraphWorld: Fake Graphs Bring Real Insights for GNNs. KDD (2022)
Oleksandr Ferludin, Arno Eigenwillig, Martin Blais, Dustin Zelle, Jan Pfeifer, Alvaro Sanchez-Gonzalez, Wai Lok Sibon Li, Sami Abu-El-Haija, Peter W. Battaglia, Neslihan Bulut, Jonathan Halcrow, Filipe Miguel Gonçalves de Almeida, Silvio Lattanzi, André Linhares, Brandon Mayer, Vahab S. Mirrokni, John Palowitch, Mihir Paradkar, Jennifer She, Anton Tsitsulin, Kevin Villela, Lisa Wang, David Wong, Bryan Perozzi
TF-GNN: Graph Neural Networks in TensorFlow. CoRR (2022)
Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. NeurIPS (2022)
John Palowitch, Anton Tsitsulin, Brandon Mayer, Bryan Perozzi
GraphWorld: Fake Graphs Bring Real Insights for GNNs. CoRR (2022)
Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller
Spectral Graph Complexity. CoRR (2022)
Judith Hermanns, Anton Tsitsulin, Marina Munkhoeva, Alexander M. Bronstein, Davide Mottin, Panagiotis Karras
GRASP: Graph Alignment Through Spectral Signatures. APWeb/WAIM (1) (2021)
Judith Hermanns, Anton Tsitsulin, Marina Munkhoeva, Alex M. Bronstein, Davide Mottin, Panagiotis Karras
GRASP: Graph Alignment through Spectral Signatures. CoRR (2021)
Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Ivan V. Oseledets, Emmanuel Müller
FREDE: Anytime Graph Embeddings. Proc. VLDB Endow. 14 (6) (2021)
Stefan Postavaru, Anton Tsitsulin, Filipe Miguel Gonçalves de Almeida, Yingtao Tian, Silvio Lattanzi, Bryan Perozzi
InstantEmbedding: Efficient Local Node Representations. CoRR (2020)
Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi
Just SLaQ When You Approximate: Accurate Spectral Distances for Web-Scale Graphs. WWW (2020)
Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller
Graph Clustering with Graph Neural Networks. CoRR (2020)
Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi
Just SLaQ When You Approximate: Accurate Spectral Distances for Web-Scale Graphs. CoRR (2020)
Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Ivan V. Oseledets, Emmanuel Müller
FREDE: Linear-Space Anytime Graph Embeddings. CoRR (2020)
Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Ivan V. Oseledets, Emmanuel Müller
The Shape of Data: Intrinsic Distance for Data Distributions. ICLR (2020)
Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller
Spectral Graph Complexity. WWW (Companion Volume) (2019)
Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Ivan V. Oseledets, Emmanuel Müller
Intrinsic Multi-scale Evaluation of Generative Models. CoRR (2019)
Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Emmanuel Müller
VERSE: Versatile Graph Embeddings from Similarity Measures. WWW (2018)
Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller
NetLSD: Hearing the Shape of a Graph. CoRR (2018)
Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Emmanuel Müller
VERSE: Versatile Graph Embeddings from Similarity Measures. CoRR (2018)
Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller
NetLSD: Hearing the Shape of a Graph. KDD (2018)
Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller
SGR: Self-Supervised Spectral Graph Representation Learning. CoRR (2018)