John Palowitch

According to our database, John Palowitch authored at least 25 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Towards Realistic Synthetic User-Generated Content: A Scaffolding Approach to Generating Online Discussions.

Krisztian Balog, John Palowitch, Barbara Ikica, Filip Radlinski, Hamidreza Alvari, Mehdi Manshadi

CoRR, 2024

SocialQuotes: Learning Contextual Roles of Social Media Quotes on the Web.

John Palowitch, Hamidreza Alvari, Mehran Kazemi, Tanvir Amin, Filip Radlinski

CoRR, 2024

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

CoRR, 2024

Where Do We Go from Here? Multi-scale Allocentric Relational Inference from Natural Spatial Descriptions.

Tzuf Paz-Argaman, Sayali Kulkarni, John Palowitch, Jason Baldridge, Reut Tsarfaty

CoRR, 2024

Where Do We Go From Here? Multi-scale Allocentric Relational Inferencefrom Natural Spatial Descriptions.

Tzuf Paz-Argaman, John Palowitch, Sayali Kulkarni, Jason Baldridge, Reut Tsarfaty

Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

Into the Unknown: Generating Geospatial Descriptions for New Environments.

Tzuf Paz-Argaman, John Palowitch, Sayali Kulkarni, Reut Tsarfaty, Jason Baldridge

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Graph Clustering with Graph Neural Networks.

Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller

J. Mach. Learn. Res., 2023

Finding Groups of Cross-Correlated Features in Bi-View Data.

Miheer Dewaskar, John Palowitch, Mark He, Michael I. Love, Andrew B. Nobel

J. Mach. Learn. Res., 2023

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

Mustafa Yasir, John Palowitch, Anton Tsitsulin, Long Tran-Thanh, Bryan Perozzi

CoRR, 2023

Graph Generative Model for Benchmarking Graph Neural Networks.

Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov

Proceedings of the International Conference on Machine Learning, 2023

2022

Scalable Privacy-enhanced Benchmark Graph Generative Model for Graph Convolutional Networks.

Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Ruslan Salakhutdinov

CoRR, 2022

TF-GNN: Graph Neural Networks in TensorFlow.

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

CoRR, 2022

Synthetic Graph Generation to Benchmark Graph Learning.

Anton Tsitsulin, Benedek Rozemberczki, John Palowitch, Bryan Perozzi

CoRR, 2022

Zero-shot Domain Adaptation of Heterogeneous Graphs via Knowledge Transfer Networks.

Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

GraphWorld: Fake Graphs Bring Real Insights for GNNs.

John Palowitch, Anton Tsitsulin, Brandon A. Mayer, Bryan Perozzi

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

Recurrent Graph Neural Networks for Rumor Detection in Online Forums.

Di Huang, Jacob Bartel, John Palowitch

CoRR, 2021

2020

Finding Stable Groups of Cross-Correlated Features in Multi-View data.

Miheer Dewaskar, John Palowitch, Mark He, Michael I. Love, Andrew B. Nobel

CoRR, 2020

Debiasing Graph Representations via Metadata-Orthogonal Training.

John Palowitch, Bryan Perozzi

Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2020

2019

MONET: Debiasing Graph Embeddings via the Metadata-Orthogonal Training Unit.

John Palowitch, Bryan Perozzi

CoRR, 2019

2018

Computing the statistical significance of optimized communities in networks.

John Palowitch

CoRR, 2018

2017

Testing-Based Community Detection Methods for Complex Networks.

John Palowitch

PhD thesis, 2017

Community Extraction in Multilayer Networks with Heterogeneous Community Structure.

James D. Wilson, John Palowitch, Shankar Bhamidi, Andrew B. Nobel

J. Mach. Learn. Res., 2017

Significance-based community detection in weighted networks.

John Palowitch, Shankar Bhamidi, Andrew B. Nobel

J. Mach. Learn. Res., 2017

2016

The Continuous Configuration Model: A Null for Community Detection on Weighted Networks.

John Palowitch, Shankar Bhamidi, Andrew B. Nobel

CoRR, 2016