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2020 – today
- 2024
[c6]Tzuf Paz-Argaman, John Palowitch, Sayali Kulkarni, Reut Tsarfaty, Jason Baldridge:
Into the Unknown: Generating Geospatial Descriptions for New Environments. ACL (Findings) 2024: 2259-2273- [c5]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: 1026-1040 - [i18]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 abs/2402.16364 (2024) - [i17]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 abs/2406.09170 (2024) - [i16]Tzuf Paz-Argaman, John Palowitch, Sayali Kulkarni, Reut Tsarfaty, Jason Baldridge:
Into the Unknown: Generating Geospatial Descriptions for New Environments. CoRR abs/2406.19967 (2024) - [i15]John Palowitch, Hamidreza Alvari, Mehran Kazemi, Tanvir Amin, Filip Radlinski:
SocialQuotes: Learning Contextual Roles of Social Media Quotes on the Web. CoRR abs/2407.16007 (2024) - [i14]Krisztian Balog, John Palowitch, Barbara Ikica, Filip Radlinski, Hamidreza Alvari, Mehdi Manshadi:
Towards Realistic Synthetic User-Generated Content: A Scaffolding Approach to Generating Online Discussions. CoRR abs/2408.08379 (2024) - 2023
- [j4]Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller:
Graph Clustering with Graph Neural Networks. J. Mach. Learn. Res. 24: 127:1-127:21 (2023) - [j3]Miheer Dewaskar, John Palowitch, Mark He, Michael I. Love, Andrew B. Nobel:
Finding Groups of Cross-Correlated Features in Bi-View Data. J. Mach. Learn. Res. 24: 398:1-398:47 (2023) - [c4]Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov:
Graph Generative Model for Benchmarking Graph Neural Networks. ICML 2023: 40175-40198 - [i13]Mustafa Yasir, John Palowitch, Anton Tsitsulin, Long Tran-Thanh, Bryan Perozzi:
Examining the Effects of Degree Distribution and Homophily in Graph Learning Models. CoRR abs/2307.08881 (2023) - 2022
- [c3]John Palowitch, Anton Tsitsulin, Brandon A. Mayer, Bryan Perozzi:
GraphWorld: Fake Graphs Bring Real Insights for GNNs. KDD 2022: 3691-3701 - [c2]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 - [i12]John Palowitch, Anton Tsitsulin, Brandon A. Mayer, Bryan Perozzi:
GraphWorld: Fake Graphs Bring Real Insights for GNNs. CoRR abs/2203.00112 (2022) - [i11]Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi:
Zero-shot Domain Adaptation of Heterogeneous Graphs via Knowledge Transfer Networks. CoRR abs/2203.02018 (2022) - [i10]Anton Tsitsulin, Benedek Rozemberczki, John Palowitch, Bryan Perozzi:
Synthetic Graph Generation to Benchmark Graph Learning. CoRR abs/2204.01376 (2022) - [i9]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:
TF-GNN: Graph Neural Networks in TensorFlow. CoRR abs/2207.03522 (2022) - [i8]Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Ruslan Salakhutdinov:
Scalable Privacy-enhanced Benchmark Graph Generative Model for Graph Convolutional Networks. CoRR abs/2207.04396 (2022) - 2021
- [i7]Di Huang, Jacob Bartel, John Palowitch:
Recurrent Graph Neural Networks for Rumor Detection in Online Forums. CoRR abs/2108.03548 (2021) - 2020
- [c1]John Palowitch, Bryan Perozzi:
Debiasing Graph Representations via Metadata-Orthogonal Training. ASONAM 2020: 435-442 - [i6]Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller:
Graph Clustering with Graph Neural Networks. CoRR abs/2006.16904 (2020) - [i5]Miheer Dewaskar
, John Palowitch, Mark He, Michael I. Love, Andrew B. Nobel:
Finding Stable Groups of Cross-Correlated Features in Multi-View data. CoRR abs/2009.05079 (2020)
2010 – 2019
- 2019
- [i4]John Palowitch, Bryan Perozzi:
MONET: Debiasing Graph Embeddings via the Metadata-Orthogonal Training Unit. CoRR abs/1909.11793 (2019) - 2018
- [i3]John Palowitch:
Computing the statistical significance of optimized communities in networks. CoRR abs/1807.02930 (2018) - 2017
- [b1]John Palowitch:
Testing-Based Community Detection Methods for Complex Networks. University of North Carolina, Chapel Hill, USA, 2017 - [j2]James D. Wilson, John Palowitch, Shankar Bhamidi, Andrew B. Nobel:
Community Extraction in Multilayer Networks with Heterogeneous Community Structure. J. Mach. Learn. Res. 18: 149:1-149:49 (2017) - [j1]John Palowitch, Shankar Bhamidi, Andrew B. Nobel:
Significance-based community detection in weighted networks. J. Mach. Learn. Res. 18: 188:1-188:48 (2017) - 2016
- [i2]John Palowitch, Shankar Bhamidi, Andrew B. Nobel:
The Continuous Configuration Model: A Null for Community Detection on Weighted Networks. CoRR abs/1601.05630 (2016) - [i1]James D. Wilson, John Palowitch, Shankar Bhamidi, Andrew B. Nobel:
Community Extraction in Multilayer Networks with Heterogeneous Community Structure. CoRR abs/1610.06511 (2016)
Coauthor Index
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last updated on 2025-01-09 00:28 CET by the dblp team
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