Learning Invariant Molecular Representation in Latent Discrete Space

Learning Invariant Molecular Representation in Latent Discrete Space

22 October 2023

Huajun Chen

Papers citing "Learning Invariant Molecular Representation in Latent Discrete Space"

18 / 18 papers shown

Title
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization Wenyu Mao Jiancan Wu Haoyang Liu Yongduo Sui Xiang Wang OOD 67 2 0 03 Aug 2024
Graph Rationalization with Environment-based Augmentations Gang Liu Tong Zhao Jiaxi Xu Te Luo Meng Jiang OOD 45 82 0 06 Jun 2022
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery -- A Focus on Affinity Prediction Problems with Noise Annotations Yuanfeng Ji Lu Zhang Jiaxiang Wu Bing Wu Long-Kai Huang ... Ping Luo Shuigeng Zhou Junzhou Huang Peilin Zhao Yatao Bian OOD 110 73 0 24 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 44 154 0 30 Dec 2021
Molecular Contrastive Learning with Chemical Element Knowledge Graph Yin Fang Qiang Zhang Haihong Yang Xiang Zhuang Shumin Deng Wen Zhang Minghai Qin Zhuo Chen Xiaohui Fan Huajun Chen 21 110 0 01 Dec 2021
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization Kartik Ahuja Ethan Caballero Dinghuai Zhang Jean-Christophe Gagnon-Audet Yoshua Bengio Ioannis Mitliagkas Irina Rish OOD 39 258 0 11 Jun 2021
Exploring Simple Siamese Representation Learning Xinlei Chen Kaiming He SSL 167 3,992 0 20 Nov 2020
Environment Inference for Invariant Learning Elliot Creager J. Jacobsen R. Zemel OOD 45 376 0 14 Oct 2020
Bootstrap your own latent: A new approach to self-supervised Learning Jean-Bastien Grill Florian Strub Florent Altché Corentin Tallec Pierre Harvey Richemond ... M. G. Azar Bilal Piot Koray Kavukcuoglu Rémi Munos Michal Valko SSL 249 6,718 0 13 Jun 2020
Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19 D. Gysi Ì. Valle Marinka Zitnik Asher Ameli Xiao Gan ... D. Ghiassian R. Baron Helia Sanchez J. Loscalzo Albert-László Barabási 24 438 0 15 Apr 2020
Analyzing Learned Molecular Representations for Property Prediction Kevin Kaichuang Yang Kyle Swanson Wengong Jin Connor W. Coley Philipp Eiden ... Andrew Palmer Volker Settels Tommi Jaakkola K. Jensen Regina Barzilay 70 1,305 0 02 Apr 2019
GNNExplainer: Generating Explanations for Graph Neural Networks Rex Ying Dylan Bourgeois Jiaxuan You Marinka Zitnik J. Leskovec LLMAG 109 1,300 0 10 Mar 2019
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 134 7,554 0 01 Oct 2018
Neural Discrete Representation Learning Aaron van den Oord Oriol Vinyals Koray Kavukcuoglu BDL SSL OCL 143 4,928 0 02 Nov 2017
Automatic chemical design using a data-driven continuous representation of molecules Rafael Gómez-Bombarelli Jennifer N. Wei David Duvenaud José Miguel Hernández-Lobato Benjamín Sánchez-Lengeling Dennis Sheberla J. Aguilera-Iparraguirre Timothy D. Hirzel Ryan P. Adams Alán Aspuru-Guzik 3DV 114 2,911 0 07 Oct 2016
Deep CORAL: Correlation Alignment for Deep Domain Adaptation Baochen Sun Kate Saenko OOD 47 3,123 0 06 Jul 2016
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 318 9,418 0 28 May 2015
Causal inference using invariant prediction: identification and confidence intervals J. Peters Peter Buhlmann N. Meinshausen OOD 74 961 0 06 Jan 2015