Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks

8 December 2022

Jiaqi Ma

Papers citing "Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks"

37 / 37 papers shown

Title
DCA-Bench: A Benchmark for Dataset Curation Agents Benhao Huang Yingzhuo Yu Jin Huang Xingjian Zhang Jiaqi Ma 52 1 0 11 Jun 2024
TF-GNN: Graph Neural Networks in TensorFlow Oleksandr Ferludin Arno Eigenwillig Martin J. Blais Dustin Zelle Jan Pfeifer ... Anton Tsitsulin Kevin Villela Lisa Wang David Wong Bryan Perozzi GNN 43 35 0 07 Jul 2022
Taxonomy of Benchmarks in Graph Representation Learning Renming Liu Semih Cantürk Frederik Wenkel Sarah McGuire Devin Kreuzer ... Michael Perlmutter Bastian Rieck M. Hirn Guy Wolf Ladislav Rampášek OOD 36 15 0 15 Jun 2022
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models Aarohi Srivastava Abhinav Rastogi Abhishek Rao Abu Awal Md Shoeb Abubakar Abid ... Zhuoye Zhao Zijian Wang Zijie J. Wang Zirui Wang Ziyi Wu ELM 95 1,739 0 09 Jun 2022
High Performance of Gradient Boosting in Binding Affinity Prediction Dmitrii Gavrilev Nurlybek Amangeldiuly Sergei Ivanov Evgeny Burnaev AI4CE 51 2 0 14 May 2022
GraphWorld: Fake Graphs Bring Real Insights for GNNs John Palowitch Anton Tsitsulin Brandon Mayer Bryan Perozzi GNN 222 68 0 28 Feb 2022
Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research Bernard Koch Emily L. Denton A. Hanna J. Foster 79 146 0 03 Dec 2021
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Derek Lim Felix Hohne Xiuyu Li Sijia Huang Vaishnavi Gupta Omkar Bhalerao Ser-Nam Lim 97 347 0 27 Oct 2021
Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features Jiuhai Chen Jonas W. Mueller V. Ioannidis Soji Adeshina Yangkun Wang Tom Goldstein David Wipf 66 12 0 26 Oct 2021
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models Benedek Rozemberczki P. Scherer Yixuan He G. Panagopoulos Alexander Riedel ... Oliver Kiss Ferenc Béres Guzmán López Nicolas Collignon Rik Sarkar AI4CE 34 202 0 15 Apr 2021
Dynabench: Rethinking Benchmarking in NLP Douwe Kiela Max Bartolo Yixin Nie Divyansh Kaushik Atticus Geiger ... Pontus Stenetorp Robin Jia Joey Tianyi Zhou Christopher Potts Adina Williams 130 401 0 07 Apr 2021
DIG: A Turnkey Library for Diving into Graph Deep Learning Research Meng Liu Youzhi Luo Limei Wang Yaochen Xie Haonan Yuan ... Haoran Liu Cong Fu Bora Oztekin Xuan Zhang Shuiwang Ji GNN 63 120 0 23 Mar 2021
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics Sebastian Gehrmann Tosin Adewumi Karmanya Aggarwal Pawan Sasanka Ammanamanchi Aremu Anuoluwapo ... Nishant Subramani Wei Xu Diyi Yang Akhila Yerukola Jiawei Zhou VLM 284 285 0 02 Feb 2021
Boost then Convolve: Gradient Boosting Meets Graph Neural Networks Sergei Ivanov Liudmila Prokhorenkova AI4CE 69 52 0 21 Jan 2021
Twitch Gamers: a Dataset for Evaluating Proximity Preserving and Structural Role-based Node Embeddings Benedek Rozemberczki Rik Sarkar 134 71 0 08 Jan 2021
TUDataset: A collection of benchmark datasets for learning with graphs Christopher Morris Nils M. Kriege Franka Bause Kristian Kersting Petra Mutzel Marion Neumann 162 808 0 16 Jul 2020
Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform Derek Lim Austin R. Benson 20 19 0 15 Jun 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 202 2,701 0 02 May 2020
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 297 931 0 02 Mar 2020
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 266 1,105 0 13 Feb 2020
Multi-scale Attributed Node Embedding Benedek Rozemberczki Carl Allen Rik Sarkar GNN 229 849 0 28 Sep 2019
Strategies for Pre-training Graph Neural Networks Weihua Hu Bowen Liu Joseph Gomes Marinka Zitnik Percy Liang Vijay S. Pande J. Leskovec SSL AI4CE 80 1,377 0 29 May 2019
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks Wei-Lin Chiang Xuanqing Liu Si Si Yang Li Samy Bengio Cho-Jui Hsieh GNN 111 1,268 0 20 May 2019
Understanding Attention and Generalization in Graph Neural Networks Boris Knyazev Graham W. Taylor Mohamed R. Amer GNN 91 338 0 08 May 2019
SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems Alex Jinpeng Wang Yada Pruksachatkun Nikita Nangia Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 183 2,296 0 02 May 2019
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing Sami Abu-El-Haija Bryan Perozzi Amol Kapoor N. Alipourfard Kristina Lerman Hrayr Harutyunyan Greg Ver Steeg Aram Galstyan GNN 79 895 0 30 Apr 2019
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 169 4,303 0 06 Mar 2019
Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorization Ankur Padia K. Kalpakis Francis Ferraro Timothy W. Finin 118 17 0 08 Feb 2019
Datasheets for Datasets Timnit Gebru Jamie Morgenstern Briana Vecchione Jennifer Wortman Vaughan Hanna M. Wallach Hal Daumé Kate Crawford 217 2,158 0 23 Mar 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 319 19,991 0 30 Oct 2017
DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning Wenhan Xiong Thi-Lan-Giao Hoang William Yang Wang 45 720 0 20 Jul 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 403 15,066 0 07 Jun 2017
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 296 1,808 0 02 Mar 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 364 1,817 0 25 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 447 28,901 0 09 Sep 2016
Revisiting Semi-Supervised Learning with Graph Embeddings Zhilin Yang William W. Cohen Ruslan Salakhutdinov GNN SSL 150 2,081 0 29 Mar 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 850 149,474 0 22 Dec 2014