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OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs


Mar 17, 2021
Weihua Hu, Matthias Fey, Hongyu Ren, Maho Nakata, Yuxiao Dong, Jure Leskovec

* KDD Cup 2021: https://ogb.stanford.edu/kddcup2021/ 

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ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations


Mar 02, 2021
Weihua Hu, Muhammed Shuaibi, Abhishek Das, Siddharth Goyal, Anuroop Sriram, Jure Leskovec, Devi Parikh, C. Lawrence Zitnick


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WILDS: A Benchmark of in-the-Wild Distribution Shifts


Dec 14, 2020
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang


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The Open Catalyst 2020 (OC20) Dataset and Community Challenges


Oct 20, 2020
Lowik Chanussot, Abhishek Das, Siddharth Goyal, Thibaut Lavril, Muhammed Shuaibi, Morgane Riviere, Kevin Tran, Javier Heras-Domingo, Caleb Ho, Weihua Hu, Aini Palizhati, Anuroop Sriram, Brandon Wood, Junwoong Yoon, Devi Parikh, C. Lawrence Zitnick, Zachary Ulissi

* 28 pages, 10 figures, submitted to ACS Catalysis 

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An Introduction to Electrocatalyst Design using Machine Learning for Renewable Energy Storage


Oct 14, 2020
C. Lawrence Zitnick, Lowik Chanussot, Abhishek Das, Siddharth Goyal, Javier Heras-Domingo, Caleb Ho, Weihua Hu, Thibaut Lavril, Aini Palizhati, Morgane Riviere, Muhammed Shuaibi, Anuroop Sriram, Kevin Tran, Brandon Wood, Junwoong Yoon, Devi Parikh, Zachary Ulissi

* 27 pages 

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Open Graph Benchmark: Datasets for Machine Learning on Graphs


May 02, 2020
Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, Jure Leskovec


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Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddings


Feb 29, 2020
Hongyu Ren, Weihua Hu, Jure Leskovec

* ICLR 2020 

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Pre-training Graph Neural Networks


May 29, 2019
Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay Pande, Jure Leskovec


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Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels


Oct 30, 2018
Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor Tsang, Masashi Sugiyama

* NIPS 2018 camera-ready version 

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How Powerful are Graph Neural Networks?


Oct 01, 2018
Keyulu Xu, Weihua Hu, Jure Leskovec, Stefanie Jegelka


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Does Distributionally Robust Supervised Learning Give Robust Classifiers?


Jul 22, 2018
Weihua Hu, Gang Niu, Issei Sato, Masashi Sugiyama

* ICML 2018 camera-ready (final submission version) 

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Learning from Complementary Labels


Nov 12, 2017
Takashi Ishida, Gang Niu, Weihua Hu, Masashi Sugiyama

* NIPS 2017 camera-ready version 

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Learning Discrete Representations via Information Maximizing Self-Augmented Training


Jun 14, 2017
Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto, Masashi Sugiyama

* To appear at ICML 2017 

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