MoleculeNet: A Benchmark for Molecular Machine Learning

2 March 2017

Papers citing "MoleculeNet: A Benchmark for Molecular Machine Learning"

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Title
Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning Dasol Hwang Jinyoung Park Sunyoung Kwon KyungHyun Kim Jung-Woo Ha Hyunwoo J. Kim OOD SSL 22 8 0 01 Mar 2021
A Genetic Algorithm with Tree-structured Mutation for Hyperparameter Optimisation of Graph Neural Networks Yingfang Yuan Wenjun Wang Wei Pang 31 9 0 24 Feb 2021
Self-Supervised Learning of Graph Neural Networks: A Unified Review Yaochen Xie Zhao Xu Jingtun Zhang Zhengyang Wang Shuiwang Ji SSL 36 324 0 22 Feb 2021
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development Kexin Huang Tianfan Fu Wenhao Gao Yue Zhao Yusuf Roohani J. Leskovec Connor W. Coley Cao Xiao Jimeng Sun Marinka Zitnik OOD LM&MA 33 261 0 18 Feb 2021
Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing Jan Toenshoff Martin Ritzert Hinrikus Wolf Martin Grohe GNN 84 28 0 17 Feb 2021
Few-Shot Graph Learning for Molecular Property Prediction Zhichun Guo Chuxu Zhang W. Yu John E. Herr Olaf Wiest Meng Jiang Nitesh V. Chawla AI4CE 119 170 0 16 Feb 2021
Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent Ajaykrishna Karthikeyan Naman Jain Nagarajan Natarajan Prateek Jain MQ 16 13 0 15 Feb 2021
Artificial Intelligence based Autonomous Molecular Design for Medical Therapeutic: A Perspective R. P. Joshi Neeraj Kumar 16 2 0 10 Feb 2021
Spherical Message Passing for 3D Graph Networks Yi Liu Limei Wang Meng Liu Xuan Zhang Bora Oztekin Shuiwang Ji GNN 22 197 0 09 Feb 2021
Generative Models as Distributions of Functions Emilien Dupont Yee Whye Teh Arnaud Doucet 22 103 0 09 Feb 2021
Graph Energy-based Model for Substructure Preserving Molecular Design Ryuichiro Hataya Hideki Nakayama Kazuki Yoshizoe 36 6 0 09 Feb 2021
GraphEBM: Molecular Graph Generation with Energy-Based Models Meng Liu Keqiang Yan Bora Oztekin Shuiwang Ji 24 84 0 31 Jan 2021
Learning Parametrised Graph Shift Operators George Dasoulas J. Lutzeyer Michalis Vazirgiannis OOD 19 21 0 25 Jan 2021
A Novel Genetic Algorithm with Hierarchical Evaluation Strategy for Hyperparameter Optimisation of Graph Neural Networks Yingfang Yuan Wenjun Wang George Macleod Coghill Wei Pang 13 15 0 22 Jan 2021
Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties T. Xie A. France-Lanord Yanming Wang Jeffrey Lopez M. Stolberg ... Graham M. Leverick Rafael Gómez-Bombarelli Jeremiah A. Johnson Y. Shao-horn Jeffrey C. Grossman 33 41 0 13 Jan 2021
Graph Networks with Spectral Message Passing Kimberly L. Stachenfeld Jonathan Godwin Peter W. Battaglia 33 12 0 31 Dec 2020
Learn molecular representations from large-scale unlabeled molecules for drug discovery Pengyong Li Jun Wang Yixuan Qiao Hao Chen Yihuan Yu Xiaojun Yao Peng Gao Guotong Xie Sen Song GNN 27 28 0 21 Dec 2020
LieTransformer: Equivariant self-attention for Lie Groups M. Hutchinson Charline Le Lan Sheheryar Zaidi Emilien Dupont Yee Whye Teh Hyunjik Kim 26 111 0 20 Dec 2020
Breaking the Expressive Bottlenecks of Graph Neural Networks Mingqi Yang Yanming Shen Heng Qi Baocai Yin 30 10 0 14 Dec 2020
ATOM3D: Tasks On Molecules in Three Dimensions Raphael J. L. Townshend M. Vögele Patricia Suriana Alexander Derry Alexander Powers ... Brandon M. Anderson Stephan Eismann Risi Kondor Russ Altman R. Dror AI4CE 19 118 0 07 Dec 2020
Reprogramming Language Models for Molecular Representation Learning R. Vinod Pin-Yu Chen Payel Das AAML OOD 32 14 0 07 Dec 2020
Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery Zhengyang Wang Meng Liu Youzhi Luo Zhao Xu Yaochen Xie ... Lei Cai Q. Qi Zhuoning Yuan Tianbao Yang Shuiwang Ji 36 100 0 02 Dec 2020
HydroNet: Benchmark Tasks for Preserving Intermolecular Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data Sutanay Choudhury Jenna A. Bilbrey Logan T. Ward S. Xantheas Ian Foster Josef Heindel Ben Blaiszik Marcus Schwarting 32 3 0 30 Nov 2020
Graph convolutions that can finally model local structure Rémy Brossard Oriel Frigo David Dehaene GNN 37 48 0 30 Nov 2020
Molecular representation learning with language models and domain-relevant auxiliary tasks Benedek Fabian T. Edlich H. Gaspar Marwin H. S. Segler Joshua Meyers Marco Fiscato Mohamed Ahmed 13 124 0 26 Nov 2020
Bayesian Graph Neural Networks for Molecular Property Prediction George Lamb Brooks Paige 23 12 0 25 Nov 2020
Attention-Based Learning on Molecular Ensembles Kangway V Chuang Michael J. Keiser 22 8 0 25 Nov 2020
Message Passing Networks for Molecules with Tetrahedral Chirality L. Pattanaik O. Ganea Ian Coley K. Jensen W. Green Connor W. Coley GNN 19 23 0 24 Nov 2020
A Large-Scale Database for Graph Representation Learning Scott Freitas Yuxiao Dong Joshua Neil Duen Horng Chau PINN GNN 24 57 0 16 Nov 2020
Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures Shuo-feng Zhang Yang Liu Lei Xie GNN 24 60 0 15 Nov 2020
Explaining Deep Graph Networks with Molecular Counterfactuals Danilo Numeroso D. Bacciu 13 10 0 09 Nov 2020
Graph Kernels: State-of-the-Art and Future Challenges Karsten M. Borgwardt Elisabetta Ghisu Felipe Llinares-López Leslie O’Bray Bastian Alexander Rieck AI4TS 31 102 0 07 Nov 2020
Co-embedding of Nodes and Edges with Graph Neural Networks Xiaodong Jiang Ronghang Zhu Pengsheng Ji Sheng Li GNN 14 74 0 25 Oct 2020
Convex Polytope Trees Mohammadreza Armandpour Mingyuan Zhou 17 1 0 21 Oct 2020
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction Seyone Chithrananda Gabriel Grand Bharath Ramsundar AI4CE 37 389 0 19 Oct 2020
Predicting Chemical Properties using Self-Attention Multi-task Learning based on SMILES Representation Sangrak Lim Yong Oh Lee 27 17 0 19 Oct 2020
Neuralizing Efficient Higher-order Belief Propagation Mohammed Haroon Dupty W. Lee 29 7 0 19 Oct 2020
Gini in a Bottleneck: Sparse Molecular Representations for Graph Convolutional Neural Networks Ryan Henderson Djork-Arné Clevert F. Montanari GNN 8 0 0 09 Oct 2020
Olympus: a benchmarking framework for noisy optimization and experiment planning Florian Hase Matteo Aldeghi Riley J. Hickman L. Roch M. Christensen Elena Liles J. Hein Alán Aspuru-Guzik 17 58 0 08 Oct 2020
Evaluating Progress on Machine Learning for Longitudinal Electronic Healthcare Data David R. Bellamy Leo Anthony Celi Andrew L. Beam LM&MA OOD 21 23 0 02 Oct 2020
Gaussian Process Molecule Property Prediction with FlowMO Henry B. Moss Ryan-Rhys Griffiths 21 23 0 02 Oct 2020
Information Obfuscation of Graph Neural Networks Peiyuan Liao Han Zhao Keyulu Xu Tommi Jaakkola Geoffrey J. Gordon Stefanie Jegelka Ruslan Salakhutdinov AAML 23 34 0 28 Sep 2020
Improving Graph Property Prediction with Generalized Readout Functions Eric Alcaide OOD AI4CE 21 0 0 21 Sep 2020
Chemical Property Prediction Under Experimental Biases Yang Liu H. Kashima AI4CE 33 1 0 18 Sep 2020
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training Tianle Cai Shengjie Luo Keyulu Xu Di He Tie-Yan Liu Liwei Wang GNN 32 158 0 07 Sep 2020
Graph Neural Network Architecture Search for Molecular Property Prediction Shengli Jiang Prasanna Balaprakash GNN AI4CE 11 34 0 27 Aug 2020
Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties Benjamin Kurt Miller Mario Geiger Tess E. Smidt Frank Noé 16 75 0 19 Aug 2020
Degree-Quant: Quantization-Aware Training for Graph Neural Networks Shyam A. Tailor Javier Fernandez-Marques Nicholas D. Lane GNN MQ 21 141 0 11 Aug 2020
MathNet: Haar-Like Wavelet Multiresolution-Analysis for Graph Representation and Learning Xuebin Zheng Bingxin Zhou Ming Li Yu Guang Wang Junbin Gao 22 2 0 22 Jul 2020
A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data Matthew B. A. McDermott Bret A. Nestor Evan Kim Wancong Zhang Anna Goldenberg Peter Szolovits Marzyeh Ghassemi Csail AI4TS 14 15 0 20 Jul 2020