Bryan Perozzi - RankMe

119 papers A* 30A 7B 4Journal 69Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	AgentsNet: Coordination and Collaborative Reasoning in Multi-Agent LLMs. CoRR Florian Grötschla, Luis Müller, Jan Tönshoff, Mikhail Galkin, Bryan Perozzi
2025	A*	`conf`	Best of Both Worlds: Advantages of Hybrid Graph Sequence Models. ICML Ali Behrouz, Ali Parviz, Mahdi Karami, Clayton Sanford, Bryan Perozzi, Vahab Mirrokni
2025	J	`jnl`	GraphBench: Next-generation graph learning benchmarking. CoRR Timo Stoll, Chendi Qian, Ben Finkelshtein, Ali Parviz, Darius Weber, Fabrizio Frasca, Hadar Shavit, Antoine Siraudin, Arman Mielke, Marie Anastacio, Erik Müller, Maya Bechler-Speicher, Michael M. Bronstein, Mikhail Galkin, Holger H. Hoos, Mathias Niepert, Bryan Perozzi, Jan Tönshoff, Christopher Morris
2025	J	`jnl`	Is it Bigger than a Breadbox: Efficient Cardinality Estimation for Real World Workloads. CoRR Zixuan Yi, Sami Abu-El-Haija, Yawen Wang, Teja Vemparala, Yannis Chronis, Yu Gan, Michael Burrows, Carsten Binnig, Bryan Perozzi, Ryan Marcus, Fatma Özcan
2025	J	`jnl`	Large-Scale Graph Building in Dynamic Environments: Low Latency and High Quality. CoRR Filipe Miguel Gonçalves de Almeida, CJ Carey, Hendrik Fichtenberger, Jonathan Halcrow, Silvio Lattanzi, André Linhares, Tao Meng, Ashkan Norouzi-Fard, Nikos Parotsidis, Bryan Perozzi, David Simcha
2025	—	`conf`	Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks. ICML (Position Papers) 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
2025	J	`jnl`	Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks. CoRR 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
2025	A*	`conf`	Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning. ICLR Bahare Fatemi, Mehran Kazemi, Anton Tsitsulin, Karishma Malkan, Jinyeong Yim, John Palowitch, Sungyong Seo, Jonathan Halcrow, Bryan Perozzi
2024	J	`jnl`	Best of Both Worlds: Advantages of Hybrid Graph Sequence Models. CoRR Ali Behrouz, Ali Parviz, Mahdi Karami, Clayton Sanford, Bryan Perozzi, Vahab Mirrokni
2024	J	`jnl`	Don't Forget to Connect! Improving RAG with Graph-based Reranking. CoRR Jialin Dong, Bahare Fatemi, Bryan Perozzi, Lin F. Yang, Anton Tsitsulin
2024	J	`jnl`	General Geospatial Inference with a Population Dynamics Foundation Model. CoRR Mohit Agarwal, Mimi Sun, Chaitanya Kamath, Arbaaz Muslim, Prithul Sarker, Joydeep Paul, Hector Yee, Marcin Sieniek, Kim Philipp Jablonski, Yael Mayer, David Fork, Sheila de Guia, Jamie McPike, Adam Boulanger, Tomer Shekel, David Schottlander, Yao Xiao, Manjit Chakravarthy Manukonda, Yun Liu, Neslihan Bulut, Sami Abu-El-Haija, Arno Eigenwillig, Parth Kothari, Bryan Perozzi, Monica Bharel, Von Nguyen, Luke Barrington, Niv Efron, Yossi Matias, Greg Corrado, Krish Eswaran, Shruthi Prabhakara, Shravya Shetty, Gautam Prasad
2024	A*	`conf`	Graph Reasoning with LLMs (GReaL). KDD Anton Tsitsulin, Bryan Perozzi, Bahare Fatemi, Jonathan J. Halcrow
2024	J	`jnl`	Let Your Graph Do the Talking: Encoding Structured Data for LLMs. CoRR Bryan Perozzi, Bahare Fatemi, Dustin Zelle, Anton Tsitsulin, Seyed Mehran Kazemi, Rami Al-Rfou, Jonathan Halcrow
2024	A*	`conf`	Talk like a Graph: Encoding Graphs for Large Language Models. ICLR Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi
2024	J	`jnl`	Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning. CoRR Bahare Fatemi, Mehran Kazemi, Anton Tsitsulin, Karishma Malkan, Jinyeong Yim, John Palowitch, Sungyong Seo, Jonathan Halcrow, Bryan Perozzi
2024	A*	`conf`	Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights. NeurIPS Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang
2024	J	`jnl`	Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights. CoRR Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang
2024	A*	`conf`	Understanding Transformer Reasoning Capabilities via Graph Algorithms. NeurIPS Clayton Sanford, Bahare Fatemi, Ethan Hall, Anton Tsitsulin, Mehran Kazemi, Jonathan Halcrow, Bryan Perozzi, Vahab Mirrokni
2024	J	`jnl`	Understanding Transformer Reasoning Capabilities via Graph Algorithms. CoRR Clayton Sanford, Bahare Fatemi, Ethan Hall, Anton Tsitsulin, Seyed Mehran Kazemi, Jonathan Halcrow, Bryan Perozzi, Vahab Mirrokni
2023	J	`jnl`	Examining the Effects of Degree Distribution and Homophily in Graph Learning Models. CoRR Mustafa Yasir, John Palowitch, Anton Tsitsulin, Long Tran-Thanh, Bryan Perozzi
2023	J	`jnl`	Explaining and Adapting Graph Conditional Shift. CoRR Qi Zhu, Yizhu Jiao, Natalia Ponomareva, Jiawei Han, Bryan Perozzi
2023	J	`jnl`	Graph Clustering with Graph Neural Networks. J. Mach. Learn. Res. Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller
2023	A*	`conf`	Graph Generative Model for Benchmarking Graph Neural Networks. ICML Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov
2023	A*	`conf`	Graph Neural Networks in TensorFlow. KDD Bryan Perozzi, Sami Abu-El-Haija, Anton Tsitsulin
2023	A*	`conf`	HUGE: Huge Unsupervised Graph Embeddings with TPUs. KDD Brandon A. Mayer, Anton Tsitsulin, Hendrik Fichtenberger, Jonathan Halcrow, Bryan Perozzi
2023	J	`jnl`	HUGE: Huge Unsupervised Graph Embeddings with TPUs. CoRR Brandon A. Mayer, Anton Tsitsulin, Hendrik Fichtenberger, Jonathan Halcrow, Bryan Perozzi
2023	A*	`conf`	HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. SIGIR Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng
2023	J	`jnl`	HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. CoRR Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng
2023	A*	`conf`	Learning Large Graph Property Prediction via Graph Segment Training. NeurIPS Kaidi Cao, Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis, Jure Leskovec, Bryan Perozzi
2023	J	`jnl`	Learning Large Graph Property Prediction via Graph Segment Training. CoRR Kaidi Cao, Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis, Jure Leskovec, Bryan Perozzi
2023	A	`conf`	SubMix: Learning to Mix Graph Sampling Heuristics. UAI Sami Abu-El-Haija, Joshua V. Dillon, Bahare Fatemi, Kyriakos Axiotis, Neslihan Bulut, Johannes Gasteiger, Bryan Perozzi, MohammadHossein Bateni
2023	J	`jnl`	Tackling Provably Hard Representative Selection via Graph Neural Networks. Trans. Mach. Learn. Res. Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, MohammadHossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab Mirrokni
2023	J	`jnl`	Talk like a Graph: Encoding Graphs for Large Language Models. CoRR Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi
2023	J	`jnl`	The Graph Lottery Ticket Hypothesis: Finding Sparse, Informative Graph Structure. CoRR Anton Tsitsulin, Bryan Perozzi
2023	A*	`conf`	TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs. NeurIPS Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Michael Burrows, Charith Mendis, Bryan Perozzi
2023	J	`jnl`	TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs. CoRR Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Charith Mendis, Bryan Perozzi
2023	J	`jnl`	UGSL: A Unified Framework for Benchmarking Graph Structure Learning. CoRR Bahare Fatemi, Sami Abu-El-Haija, Anton Tsitsulin, Seyed Mehran Kazemi, Dustin Zelle, Neslihan Bulut, Jonathan Halcrow, Bryan Perozzi
2023	—	`conf`	Unsupervised Embedding Quality Evaluation. TAG-ML Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi
2023	J	`jnl`	Unsupervised Embedding Quality Evaluation. CoRR Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi
2022	A*	`conf`	Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. NeurIPS Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong
2022	J	`jnl`	Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. CoRR Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong
2022	A*	`conf`	GraphWorld: Fake Graphs Bring Real Insights for GNNs. KDD John Palowitch, Anton Tsitsulin, Brandon A. Mayer, Bryan Perozzi
2022	J	`jnl`	GraphWorld: Fake Graphs Bring Real Insights for GNNs. CoRR John Palowitch, Anton Tsitsulin, Brandon A. Mayer, Bryan Perozzi
2022	J	`jnl`	Machine Learning on Graphs: A Model and Comprehensive Taxonomy. J. Mach. Learn. Res. Ines Chami, Sami Abu-El-Haija, Bryan Perozzi, Christopher Ré, Kevin Murphy
2022	J	`jnl`	On Classification Thresholds for Graph Attention with Edge Features. CoRR Kimon Fountoulakis, Dake He, Silvio Lattanzi, Bryan Perozzi, Anton Tsitsulin, Shenghao Yang
2022	J	`jnl`	Scalable Privacy-enhanced Benchmark Graph Generative Model for Graph Convolutional Networks. CoRR Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Ruslan Salakhutdinov
2022	J	`jnl`	Synthetic Graph Generation to Benchmark Graph Learning. CoRR Anton Tsitsulin, Benedek Rozemberczki, John Palowitch, Bryan Perozzi
2022	J	`jnl`	TF-GNN: Graph Neural Networks in TensorFlow. CoRR 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 A. Mayer, Vahab S. Mirrokni, John Palowitch, Mihir Paradkar, Jennifer She, Anton Tsitsulin, Kevin Villela, Lisa Wang, David Wong, Bryan Perozzi
2022	J	`jnl`	Tackling Provably Hard Representative Selection via Graph Neural Networks. CoRR Seyed Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, MohammadHossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab S. Mirrokni
2022	J	`jnl`	Zero-shot Domain Adaptation of Heterogeneous Graphs via Knowledge Transfer Networks. CoRR Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi
2022	A*	`conf`	Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks. NeurIPS Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi
2021	A*	`conf`	Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning. ICLR Elan Sopher Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan
2021	J	`jnl`	Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning. CoRR Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan
2021	A*	`conf`	Pathfinder Discovery Networks for Neural Message Passing. WWW Benedek Rozemberczki, Peter Englert, Amol Kapoor, Martin Blais, Bryan Perozzi
2021	A*	`conf`	Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data. NeurIPS Qi Zhu, Natalia Ponomareva, Jiawei Han, Bryan Perozzi
2021	J	`jnl`	Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data. CoRR Qi Zhu, Natalia Ponomareva, Jiawei Han, Bryan Perozzi
2020	B	`conf`	Debiasing Graph Representations via Metadata-Orthogonal Training. ASONAM John Palowitch, Bryan Perozzi
2020	J	`jnl`	Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural Networks. CoRR Amol Kapoor, Xue Ben, Luyang Liu, Bryan Perozzi, Matt Barnes, Martin Blais, Shawn O'Banion
2020	A*	`conf`	Grale: Designing Networks for Graph Learning. KDD Jonathan Halcrow, Alexandru Mosoi, Sam Ruth, Bryan Perozzi
2020	J	`jnl`	Grale: Designing Networks for Graph Learning. CoRR Jonathan Halcrow, Alexandru Mosoi, Sam Ruth, Bryan Perozzi
2020	J	`jnl`	Graph Clustering with Graph Neural Networks. CoRR Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller
2020	—	`conf`	Graph Embedding with Personalized Context Distribution. WWW (Companion Volume) Di Huang, Zihao He, Yuzhong Huang, Kexuan Sun, Sami Abu-El-Haija, Bryan Perozzi, Kristina Lerman, Fred Morstatter, Aram Galstyan
2020	J	`jnl`	InstantEmbedding: Efficient Local Node Representations. CoRR Stefan Postavaru, Anton Tsitsulin, Filipe Miguel Gonçalves de Almeida, Yingtao Tian, Silvio Lattanzi, Bryan Perozzi
2020	A*	`conf`	Just SLaQ When You Approximate: Accurate Spectral Distances for Web-Scale Graphs. WWW Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi
2020	J	`jnl`	Just SLaQ When You Approximate: Accurate Spectral Distances for Web-Scale Graphs. CoRR Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi
2020	J	`jnl`	Machine Learning on Graphs: A Model and Comprehensive Taxonomy. CoRR Ines Chami, Sami Abu-El-Haija, Bryan Perozzi, Christopher Ré, Kevin Murphy
2020	J	`jnl`	Pathfinder Discovery Networks for Neural Message Passing. CoRR Benedek Rozemberczki, Peter Englert, Amol Kapoor, Martin Blais, Bryan Perozzi
2020	A*	`conf`	Scaling Graph Neural Networks with Approximate PageRank. KDD Aleksandar Bojchevski, Johannes Klicpera, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rózemberczki, Michal Lukasik, Stephan Günnemann
2020	J	`jnl`	Scaling Graph Neural Networks with Approximate PageRank. CoRR Aleksandar Bojchevski, Johannes Klicpera, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rózemberczki, Michal Lukasik, Stephan Günnemann
2019	A*	`conf`	DDGK: Learning Graph Representations for Deep Divergence Graph Kernels. WWW Rami Al-Rfou, Bryan Perozzi, Dustin Zelle
2019	J	`jnl`	DDGK: Learning Graph Representations for Deep Divergence Graph Kernels. CoRR Rami Al-Rfou, Dustin Zelle, Bryan Perozzi
2019	A*	`conf`	Is a Single Embedding Enough? Learning Node Representations that Capture Multiple Social Contexts. WWW Alessandro Epasto, Bryan Perozzi
2019	J	`jnl`	Is a Single Embedding Enough? Learning Node Representations that Capture Multiple Social Contexts. CoRR Alessandro Epasto, Bryan Perozzi
2019	J	`jnl`	MONET: Debiasing Graph Embeddings via the Metadata-Orthogonal Training Unit. CoRR John Palowitch, Bryan Perozzi
2019	A*	`conf`	MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. ICML Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan
2019	J	`jnl`	MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. CoRR Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Hrayr Harutyunyan, Nazanin Alipourfard, Kristina Lerman, Greg Ver Steeg, Aram Galstyan
2019	A	`conf`	N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification. UAI Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, Joonseok Lee
2019	—	`conf`	Social Relation Inference via Label Propagation. ECIR (1) Yingtao Tian, Haochen Chen, Bryan Perozzi, Muhao Chen, Xiaofei Sun, Steven Skiena
2018	J	`jnl`	A Tutorial on Network Embeddings. CoRR Haochen Chen, Bryan Perozzi, Rami Al-Rfou, Steven Skiena
2018	J	`jnl`	Discovering Communities and Anomalies in Attributed Graphs: Interactive Visual Exploration and Summarization. ACM Trans. Knowl. Discov. Data Bryan Perozzi, Leman Akoglu
2018	A	`conf`	Enhanced Network Embeddings via Exploiting Edge Labels. CIKM Haochen Chen, Xiaofei Sun, Yingtao Tian, Bryan Perozzi, Muhao Chen, Steven Skiena
2018	J	`jnl`	Enhanced Network Embeddings via Exploiting Edge Labels. CoRR Haochen Chen, Xiaofei Sun, Yingtao Tian, Bryan Perozzi, Muhao Chen, Steven Skiena
2018	A*	`conf`	HARP: Hierarchical Representation Learning for Networks. AAAI Haochen Chen, Bryan Perozzi, Yifan Hu, Steven Skiena
2018	J	`jnl`	N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification. CoRR Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, Joonseok Lee
2018	A*	`conf`	Watch Your Step: Learning Node Embeddings via Graph Attention. NeurIPS Sami Abu-El-Haija, Bryan Perozzi, Rami Al-Rfou, Alexander A. Alemi
2017	J	`jnl`	ASYMP: Fault-tolerant Mining of Massive Graphs. CoRR Eduardo Fleury, Silvio Lattanzi, Vahab S. Mirrokni, Bryan Perozzi
2017	B	`conf`	Don't Walk, Skip!: Online Learning of Multi-scale Network Embeddings. ASONAM Bryan Perozzi, Vivek Kulkarni, Haochen Chen, Steven Skiena
2017	J	`jnl`	HARP: Hierarchical Representation Learning for Networks. CoRR Haochen Chen, Bryan Perozzi, Yifan Hu, Steven Skiena
2017	A	`conf`	Learning Edge Representations via Low-Rank Asymmetric Projections. CIKM Sami Abu-El-Haija, Bryan Perozzi, Rami Al-Rfou
2017	J	`jnl`	Learning Edge Representations via Low-Rank Asymmetric Projections. CoRR Sami Abu-El-Haija, Bryan Perozzi, Rami Al-Rfou
2017	J	`jnl`	Ties That Bind - Characterizing Classes by Attributes and Social Ties. CoRR Aria Rezaei, Bryan Perozzi, Leman Akoglu
2017	—	`conf`	Ties That Bind: Characterizing Classes by Attributes and Social Ties. WWW (Companion Volume) Aria Rezaei, Bryan Perozzi, Leman Akoglu
2017	J	`jnl`	Vector-based similarity measurements for historical figures. Inf. Syst. Yanqing Chen, Bryan Perozzi, Steven Skiena
2017	J	`jnl`	Watch Your Step: Learning Graph Embeddings Through Attention. CoRR Sami Abu-El-Haija, Bryan Perozzi, Rami Al-Rfou, Alex Alemi
2016	A	`conf`	Freshman or Fresher? Quantifying the Geographic Variation of Language in Online Social Media. ICWSM Vivek Kulkarni, Bryan Perozzi, Steven Skiena
2016	J	`jnl`	On the Convergent Properties of Word Embedding Methods. CoRR Yingtao Tian, Vivek Kulkarni, Bryan Perozzi, Steven Skiena
2016	A	`conf`	Scalable Anomaly Ranking of Attributed Neighborhoods. SDM Bryan Perozzi, Leman Akoglu
2016	J	`jnl`	Scalable Anomaly Ranking of Attributed Neighborhoods. CoRR Bryan Perozzi, Leman Akoglu
2016	J	`jnl`	Walklets: Multiscale Graph Embeddings for Interpretable Network Classification. CoRR Bryan Perozzi, Vivek Kulkarni, Steven Skiena
2016	A*	`conf`	When Recommendation Goes Wrong: Anomalous Link Discovery in Recommendation Networks. KDD Bryan Perozzi, Michael Schueppert, Jack Saalweachter, Mayur Thakur
2015	—	`conf`	Exact Age Prediction in Social Networks. WWW (Companion Volume) Bryan Perozzi, Steven Skiena
2015	J	`jnl`	Freshman or Fresher? Quantifying the Geographic Variation of Internet Language. CoRR Vivek Kulkarni, Bryan Perozzi, Steven Skiena
2015	A	`conf`	POLYGLOT-NER: Massive Multilingual Named Entity Recognition. SDM Rami Al-Rfou, Vivek Kulkarni, Bryan Perozzi, Steven Skiena
2015	A*	`conf`	Statistically Significant Detection of Linguistic Change. WWW Vivek Kulkarni, Rami Al-Rfou, Bryan Perozzi, Steven Skiena
2015	B	`conf`	Vector-Based Similarity Measurements for Historical Figures. SISAP Yanqing Chen, Bryan Perozzi, Steven Skiena
2014	J	`jnl`	DeepWalk: Online Learning of Social Representations. CoRR Bryan Perozzi, Rami Al-Rfou, Steven Skiena
2014	A*	`conf`	DeepWalk: online learning of social representations. KDD Bryan Perozzi, Rami Al-Rfou, Steven Skiena
2014	J	`jnl`	Exploring the power of GPU's for training Polyglot language models. CoRR Vivek Kulkarni, Rami Al-Rfou', Bryan Perozzi, Steven Skiena
2014	A*	`conf`	Focused clustering and outlier detection in large attributed graphs. KDD Bryan Perozzi, Leman Akoglu, Patricia Iglesias Sánchez, Emmanuel Müller
2014	—	`conf`	Inducing Language Networks from Continuous Space Word Representations. CompleNet Bryan Perozzi, Rami Al-Rfou', Vivek Kulkarni, Steven Skiena
2014	J	`jnl`	Inducing Language Networks from Continuous Space Word Representations. CoRR Bryan Perozzi, Rami Al-Rfou, Vivek Kulkarni, Steven Skiena
2014	J	`jnl`	POLYGLOT-NER: Massive Multilingual Named Entity Recognition. CoRR Rami Al-Rfou, Vivek Kulkarni, Bryan Perozzi, Steven Skiena
2014	J	`jnl`	Scalable graph clustering with parallel approximate PageRank. Soc. Netw. Anal. Min. Bryan Perozzi, Christopher McCubbin, James T. Halbert
2014	J	`jnl`	Statistically Significant Detection of Linguistic Change. CoRR Vivek Kulkarni, Rami Al-Rfou, Bryan Perozzi, Steven Skiena
2013	B	`conf`	Polyglot: Distributed Word Representations for Multilingual NLP. CoNLL Rami Al-Rfou', Bryan Perozzi, Steven Skiena
2013	J	`jnl`	Polyglot: Distributed Word Representations for Multilingual NLP. CoRR Rami Al-Rfou, Bryan Perozzi, Steven Skiena
2013	—	`conf`	Scalable Graph Clustering with Pregel. CompleNet Bryan Perozzi, Christopher McCubbin, Spencer Beecher, James T. Halbert
2013	J	`jnl`	The Expressive Power of Word Embeddings CoRR Yanqing Chen, Bryan Perozzi, Rami Al-Rfou', Steven Skiena
2011	—	`conf`	Finding the 'Needle': Locating Interesting Nodes Using the K-shortest Paths Algorithm in MapReduce. ICDM Workshops Christopher McCubbin, Bryan Perozzi, Andrew Levine, Abdul Rahman