John Palowitch

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 26

Top Topics

Graph Representation

Statistical Significance

Community Detection

Top Venues

J. Mach. Learn. Res.

Publications

Tzuf Paz-Argaman, John Palowitch, Sayali Kulkarni, Jason Baldridge, Reut Tsarfaty
Where Do We Go From Here? Multi-scale Allocentric Relational Inferencefrom Natural Spatial Descriptions. EACL (1) (2024)
Tzuf Paz-Argaman, Sayali Kulkarni, John Palowitch, Jason Baldridge, Reut Tsarfaty
Where Do We Go from Here? Multi-scale Allocentric Relational Inference from Natural Spatial Descriptions. CoRR (2024)
Tzuf Paz-Argaman, John Palowitch, Sayali Kulkarni, Reut Tsarfaty, Jason Baldridge
Into the Unknown: Generating Geospatial Descriptions for New Environments. 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)
Tzuf Paz-Argaman, John Palowitch, Sayali Kulkarni, Reut Tsarfaty, Jason Baldridge
Into the Unknown: Generating Geospatial Descriptions for New Environments. ACL (Findings) (2024)
John Palowitch, Hamidreza Alvari, Mehran Kazemi, Tanvir Amin, Filip Radlinski
SocialQuotes: Learning Contextual Roles of Social Media Quotes on the Web. CoRR (2024)
Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov
Graph Generative Model for Benchmarking Graph Neural Networks. ICML (2023)
Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller
Graph Clustering with Graph Neural Networks. J. Mach. Learn. Res. 24 (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)
Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi
Zero-shot Domain Adaptation of Heterogeneous Graphs via Knowledge Transfer Networks. CoRR (2022)
Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Ruslan Salakhutdinov
Scalable Privacy-enhanced Benchmark Graph Generative Model for Graph Convolutional Networks. CoRR (2022)
Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi
Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks. NeurIPS (2022)
Anton Tsitsulin, Benedek Rozemberczki, John Palowitch, Bryan Perozzi
Synthetic Graph Generation to Benchmark Graph Learning. 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)
John Palowitch, Anton Tsitsulin, Brandon Mayer, Bryan Perozzi
GraphWorld: Fake Graphs Bring Real Insights for GNNs. CoRR (2022)
Di Huang, Jacob Bartel, John Palowitch
Recurrent Graph Neural Networks for Rumor Detection in Online Forums. CoRR (2021)
Miheer Dewaskar, John Palowitch, Mark He, Michael I. Love, Andrew B. Nobel
Finding Stable Groups of Cross-Correlated Features in Multi-View data. CoRR (2020)
Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller
Graph Clustering with Graph Neural Networks. CoRR (2020)
John Palowitch, Bryan Perozzi
Debiasing Graph Representations via Metadata-Orthogonal Training. ASONAM (2020)
John Palowitch, Bryan Perozzi
MONET: Debiasing Graph Embeddings via the Metadata-Orthogonal Training Unit. CoRR (2019)
John Palowitch
Computing the statistical significance of optimized communities in networks. CoRR (2018)
James D. Wilson, John Palowitch, Shankar Bhamidi, Andrew B. Nobel
Community Extraction in Multilayer Networks with Heterogeneous Community Structure. J. Mach. Learn. Res. 18 (2017)
John Palowitch, Shankar Bhamidi, Andrew B. Nobel
Significance-based community detection in weighted networks. J. Mach. Learn. Res. 18 (2017)
James D. Wilson, John Palowitch, Shankar Bhamidi, Andrew B. Nobel
Community Extraction in Multilayer Networks with Heterogeneous Community Structure. CoRR (2016)
John Palowitch, Shankar Bhamidi, Andrew B. Nobel
The Continuous Configuration Model: A Null for Community Detection on Weighted Networks. CoRR (2016)