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On the Opportunities and Risks of Foundation Models


Aug 18, 2021
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Kohd, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, Percy Liang

* Authored by the Center for Research on Foundation Models (CRFM) at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) 

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Combiner: Full Attention Transformer with Sparse Computation Cost


Jul 12, 2021
Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai


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GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings


Jun 10, 2021
Matthias Fey, Jan E. Lenssen, Frank Weichert, Jure Leskovec

* Published as a conference paper at ICML 2021 

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QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering


Apr 13, 2021
Michihiro Yasunaga, Hongyu Ren, Antoine Bosselut, Percy Liang, Jure Leskovec

* NAACL 2021. Code & data available at https://github.com/michiyasunaga/qagnn 

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Language-Agnostic Representation Learning of Source Code from Structure and Context


Mar 21, 2021
Daniel Zügner, Tobias Kirschstein, Michele Catasta, Jure Leskovec, Stephan Günnemann

* ICLR 2021 

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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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Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics


Feb 18, 2021
Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik


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Model-Agnostic Graph Regularization for Few-Shot Learning


Feb 14, 2021
Ethan Shen, Maria Brbic, Nicholas Monath, Jiaqi Zhai, Manzil Zaheer, Jure Leskovec

* NeurIPS Workshop on Meta-Learning 2020 

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Driver2vec: Driver Identification from Automotive Data


Feb 10, 2021
Jingbo Yang, Ruge Zhao, Meixian Zhu, David Hallac, Jaka Sodnik, Jure Leskovec

* 7 pages, 3 figures, 6 tables in the main text. First publisehd to 6th Workshop on Mining and Learning from Time Series (2020) 

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Open-World Semi-Supervised Learning


Feb 06, 2021
Kaidi Cao, Maria Brbic, Jure Leskovec


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Identity-aware Graph Neural Networks


Feb 05, 2021
Jiaxuan You, Jonathan Gomes-Selman, Rex Ying, Jure Leskovec

* AAAI 2021. Version with appendix 

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Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks


Jan 15, 2021
Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li

* Accepted to ICLR 2021 

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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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Design Space for Graph Neural Networks


Nov 17, 2020
Jiaxuan You, Rex Ying, Jure Leskovec

* NeurIPS 2020 (Spotlight) 

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Coresets for Robust Training of Neural Networks against Noisy Labels


Nov 15, 2020
Baharan Mirzasoleiman, Kaidi Cao, Jure Leskovec

* Advances in Neural Information Processing Systems 2020 

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F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams


Nov 09, 2020
Yen-Yu Chang, Pan Li, Rok Sosic, M. H. Afifi, Marco Schweighauser, Jure Leskovec

* WSDM 2021 

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Handling Missing Data with Graph Representation Learning


Oct 30, 2020
Jiaxuan You, Xiaobai Ma, Daisy Yi Ding, Mykel Kochenderfer, Jure Leskovec

* NeurIPS 2020 

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Graph Information Bottleneck


Oct 24, 2020
Tailin Wu, Hongyu Ren, Pan Li, Jure Leskovec

* 20 pages, 3 figures, NeurIPS 2020 

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Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphs


Oct 22, 2020
Hongyu Ren, Jure Leskovec

* NeurIPS 2020 

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Direct Multi-hop Attention based Graph Neural Network


Oct 02, 2020
Guangtao Wang, Rex Ying, Jing Huang, Jure Leskovec


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Inductive Learning on Commonsense Knowledge Graph Completion


Sep 19, 2020
Bin Wang, Guangtao Wang, Jing Huang, Jiaxuan You, Jure Leskovec, C. -C. Jay Kuo

* 10 pages, 3 figures, 7 tables 

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Distance Encoding -- Design Provably More Powerful Graph Neural Networks for Structural Representation Learning


Sep 05, 2020
Pan Li, Yanbang Wang, Hongwei Wang, Jure Leskovec


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Distance Encoding -- Design Provably More Powerful GNNs for Structural Representation Learning


Aug 31, 2020
Pan Li, Yanbang Wang, Hongwei Wang, Jure Leskovec


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OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation


Aug 17, 2020
Hongyu Ren, Yuke Zhu, Jure Leskovec, Anima Anandkumar, Animesh Garg

* UAI 2020 

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Concept Learners for Generalizable Few-Shot Learning


Jul 14, 2020
Kaidi Cao, Maria Brbic, Jure Leskovec


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Graph Structure of Neural Networks


Jul 13, 2020
Jiaxuan You, Jure Leskovec, Kaiming He, Saining Xie

* ICML 2020 

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