Perozzi, Bryan

30 publications

ICML 2025 Best of Both Worlds: Advantages of Hybrid Graph Sequence Models Ali Behrouz, Ali Parviz, Mahdi Karami, Clayton Sanford, Bryan Perozzi, Vahab Mirrokni

ICML 2025 Position: Graph Learning Will Lose Relevance Due to Poor Benchmarks Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris

ICLR 2025 Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning Bahare Fatemi, Mehran Kazemi, Anton Tsitsulin, Karishma Malkan, Jinyeong Yim, John Palowitch, Sungyong Seo, Jonathan Halcrow, Bryan Perozzi

ICMLW 2024 Can LLMs Enhance Performance Prediction for Deep Learning Models? Karthick Panner Selvam, Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Bryan Perozzi, Mats Brorsson

ICLR 2024 Talk like a Graph: Encoding Graphs for Large Language Models Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi

NeurIPS 2024 Text-Space Graph Foundation Models: Comprehensive Benchmarks and New Insights Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang

NeurIPS 2024 Understanding Transformer Reasoning Capabilities via Graph Algorithms Clayton Sanford, Bahare Fatemi, Ethan Hall, Anton Tsitsulin, Mehran Kazemi, Jonathan Halcrow, Bryan Perozzi, Vahab Mirrokni

JMLR 2023 Graph Clustering with Graph Neural Networks Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller

ICML 2023 Graph Generative Model for Benchmarking Graph Neural Networks Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov

NeurIPS 2023 Learning Large Graph Property Prediction via Graph Segment Training Kaidi Cao, Mangpo Phothilimthana, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis, Jure Leskovec, Bryan Perozzi

ICMLW 2023 Learning Large Graph Property Prediction via Graph Segment Training Kaidi Cao, Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis, Jure Leskovec, Bryan Perozzi

UAI 2023 SubMix: Learning to Mix Graph Sampling Heuristics Sami Abu-El-Haija, Joshua V. Dillon, Bahare Fatemi, Kyriakos Axiotis, Neslihan Bulut, Johannes Gasteiger, Bryan Perozzi, Mohammadhossein Bateni

TMLR 2023 Tackling Provably Hard Representative Selection via Graph Neural Networks Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, Mohammadhossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab Mirrokni

ICMLW 2023 Tackling Provably Hard Representative Selection viaGraph Neural Networks Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, Mohammadhossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab Mirrokni

NeurIPSW 2023 Talk like a Graph: Encoding Graphs for Large Language Models Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi

NeurIPSW 2023 The Graph Lottery Ticket Hypothesis: Finding Sparse, Informative Graph Structure Anton Tsitsulin, Bryan Perozzi

NeurIPS 2023 TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs Mangpo Phothilimthana, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Michael Burrows, Charith Mendis, Bryan Perozzi

ICMLW 2023 UGSL: A Unified Framework for Benchmarking Graph Structure Learning Bahare Fatemi, Sami Abu-El-Haija, Anton Tsitsulin, Mehran Kazemi, Dustin Zelle, Neslihan Bulut, Jonathan Halcrow, Bryan Perozzi

ICMLW 2023 Unsupervised Embedding Quality Evaluation Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi

NeurIPS 2022 Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong

NeurIPSW 2022 Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong

JMLR 2022 Machine Learning on Graphs: A Model and Comprehensive Taxonomy Ines Chami, Sami Abu-El-Haija, Bryan Perozzi, Christopher Ré, Kevin Murphy

NeurIPSW 2022 Synthetic Graph Generation to Benchmark Graph Learning John Palowitch, Anton Tsitsulin, Bryan Perozzi, Brandon A. Mayer

NeurIPS 2022 Zero-Shot Transfer Learning Within a Heterogeneous Graph via Knowledge Transfer Networks Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi

ICLR 2021 Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning Elan Sopher Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan

NeurIPS 2021 Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data Qi Zhu, Natalia Ponomareva, Jiawei Han, Bryan Perozzi

ICML 2019 MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan

UAI 2019 N-GCN: Multi-Scale Graph Convolution for Semi-Supervised Node Classification Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, Joonseok Lee

AAAI 2018 HARP: Hierarchical Representation Learning for Networks Haochen Chen, Bryan Perozzi, Yifan Hu, Steven Skiena

NeurIPS 2018 Watch Your Step: Learning Node Embeddings via Graph Attention Sami Abu-El-Haija, Bryan Perozzi, Rami Al-Rfou, Alexander A Alemi