Identifying Semantic Component for Robust Molecular Property Prediction

8 November 2023

Zijian Li

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Papers citing "Identifying Semantic Component for Robust Molecular Property Prediction"

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Title
GOOD: A Graph Out-of-Distribution Benchmark Shurui Gui Xiner Li Limei Wang Shuiwang Ji OOD 85 123 0 16 Jun 2022
Graph Rationalization with Environment-based Augmentations Gang Liu Tong Zhao Jiaxi Xu Te Luo Meng Jiang OOD 82 85 0 06 Jun 2022
Exploring Chemical Space with Score-based Out-of-distribution Generation Seul Lee Jaehyeong Jo Sung Ju Hwang OODD 109 80 0 06 Jun 2022
Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization Weijia Zhang Xuanhui Zhang Hanwen Deng Min-Ling Zhang 89 23 0 25 Feb 2022
Out-Of-Distribution Generalization on Graphs: A Survey Haoyang Li Xin Eric Wang Ziwei Zhang Wenwu Zhu OOD CML 117 101 0 16 Feb 2022
Discovering Invariant Rationales for Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xiangnan He Tat-Seng Chua OOD AI4CE 170 234 0 30 Jan 2022
Causal Attention for Interpretable and Generalizable Graph Classification Yongduo Sui Xiang Wang Jiancan Wu Min Lin Xiangnan He Tat-Seng Chua CML OOD 83 158 0 30 Dec 2021
OOD-GNN: Out-of-Distribution Generalized Graph Neural Network Haoyang Li Xin Eric Wang Ziwei Zhang Wenwu Zhu OODD OOD 95 104 0 07 Dec 2021
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs Shaohua Fan Xiao Wang Chuan Shi Peng Cui Bai Wang CML OOD OODD AI4CE 142 88 0 20 Nov 2021
Learning Temporally Causal Latent Processes from General Temporal Data Weiran Yao Yuewen Sun Alex Ho Changyin Sun Kun Zhang BDL CML 91 87 0 11 Oct 2021
3D Infomax improves GNNs for Molecular Property Prediction Hannes Stärk Dominique Beaini Gabriele Corso Prudencio Tossou Christian Dallago Stephan Günnemann Pietro Lio AI4CE 92 208 0 08 Oct 2021
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction Zaixin Zhang Qi Liu Hao Wang Chengqiang Lu Chee-Kong Lee SSL AI4CE 95 259 0 03 Oct 2021
GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction Shuangli Li Jingbo Zhou Tong Xu Dejing Dou Hui Xiong AI4CE 75 122 0 24 Sep 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 155 535 0 31 Aug 2021
Geometric Deep Learning on Molecular Representations Kenneth Atz F. Grisoni G. Schneider AI4CE 98 303 0 26 Jul 2021
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA Hermanni Hälvä Sylvain Le Corff Luc Lehéricy Jonathan So Yongjie Zhu Elisabeth Gassiat Aapo Hyvarinen CML 60 65 0 17 Jun 2021
Graph Domain Adaptation: A Generative View Ruichu Cai Fengzhu Wu Zijian Li Pengfei Wei Lingling Yi Kun Zhang OOD 72 38 0 14 Jun 2021
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style Julius von Kügelgen Yash Sharma Luigi Gresele Wieland Brendel Bernhard Schölkopf M. Besserve Francesco Locatello 110 317 0 08 Jun 2021
HiddenCut: Simple Data Augmentation for Natural Language Understanding with Better Generalization Jiaao Chen Dinghan Shen Weizhu Chen Diyi Yang BDL 65 48 0 31 May 2021
Deep Stable Learning for Out-Of-Distribution Generalization Xingxuan Zhang Peng Cui Renzhe Xu Linjun Zhou Yue He Zheyan Shen OOD 84 257 0 16 Apr 2021
Uncertainty Aware Semi-Supervised Learning on Graph Data Xujiang Zhao Feng Chen Shu Hu Jin-Hee Cho UQCV EDL BDL 192 139 0 24 Oct 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 311 2,752 0 02 May 2020
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax Andres Potapczynski Gabriel Loaiza-Ganem John P. Cunningham 84 30 0 19 Dec 2019
Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective Chengqiang Lu Qi Liu Chao Wang Zhenya Huang Peize Lin Lixin He AI4CE 70 193 0 25 Jun 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 120 1,416 0 29 May 2019
Disentangling Factors of Variation Using Few Labels Francesco Locatello Michael Tschannen Stefan Bauer Gunnar Rätsch Bernhard Schölkopf Olivier Bachem DRL CML CoGe 98 124 0 03 May 2019
Simplifying Graph Convolutional Networks Felix Wu Tianyi Zhang Amauri Souza Christopher Fifty Tao Yu Kilian Q. Weinberger GNN 250 3,184 0 19 Feb 2019
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD 143 1,473 0 29 Nov 2018
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 259 7,705 0 01 Oct 2018
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 518 1,990 0 09 Jun 2018
Relational inductive biases, deep learning, and graph networks Peter W. Battaglia Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez V. Zambaldi ... Pushmeet Kohli M. Botvinick Oriol Vinyals Yujia Li Razvan Pascanu AI4CE NAI 769 3,132 0 04 Jun 2018
Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning Aapo Hyvarinen Hiroaki Sasaki Richard Turner OOD CML 100 331 0 22 May 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 484 20,265 0 30 Oct 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 516 15,369 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 343 1,838 0 02 Mar 2017
Categorical Reparameterization with Gumbel-Softmax Eric Jang S. Gu Ben Poole BDL 363 5,390 0 03 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 679 29,183 0 09 Sep 2016