MoleculeNet: A Benchmark for Molecular Machine Learning

2 March 2017

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

50 / 803 papers shown

Title
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs Dasol Hwang Jinyoung Park Sunyoung Kwon KyungHyun Kim Jung-Woo Ha Hyunwoo J. Kim 44 67 0 16 Jul 2020
OrbNet: Deep Learning for Quantum Chemistry Using Symmetry-Adapted Atomic-Orbital Features Zhuoran Qiao Matthew Welborn Anima Anandkumar F. Manby Thomas F. Miller AI4CE 24 214 0 15 Jul 2020
Efficient Conformal Prediction via Cascaded Inference with Expanded Admission Adam Fisch Tal Schuster Tommi Jaakkola Regina Barzilay 6 1 0 06 Jul 2020
Data-Driven Discovery of Molecular Photoswitches with Multioutput Gaussian Processes Ryan-Rhys Griffiths Jake L. Greenfield Aditya R. Thawani Arian R. Jamasb Henry B. Moss Anthony Bourached Penelope Jones William McCorkindale Alexander A. Aldrick Matthew J. Fuchter Alpha A. Lee 30 13 0 28 Jun 2020
Hierarchical Inter-Message Passing for Learning on Molecular Graphs Matthias Fey Jan-Gin Yuen F. Weichert GNN 39 86 0 22 Jun 2020
Self-Supervised Graph Transformer on Large-Scale Molecular Data Yu Rong Yatao Bian Tingyang Xu Wei-yang Xie Ying Wei Wenbing Huang Junzhou Huang AI4CE 21 25 0 18 Jun 2020
A benchmark study on reliable molecular supervised learning via Bayesian learning Doyeong Hwang Grace Lee Hanseok Jo Seyoul Yoon Seongok Ryu 22 9 0 12 Jun 2020
Weisfeiler-Lehman Embedding for Molecular Graph Neural Networks Katsuhiko Ishiguro Kenta Oono K. Hayashi GNN 30 4 0 12 Jun 2020
GEOM: Energy-annotated molecular conformations for property prediction and molecular generation Simon Axelrod Rafael Gómez-Bombarelli 3DV AI4CE 31 206 0 09 Jun 2020
Graph-Aware Transformer: Is Attention All Graphs Need? Sang-yong Yoo Young-Seok Kim Kang Lee Kuhwan Jeong Junhwi Choi Hoshik Lee Y. S. Choi GNN 22 11 0 09 Jun 2020
On the Bottleneck of Graph Neural Networks and its Practical Implications Uri Alon Eran Yahav GNN 46 662 0 09 Jun 2020
Enforcing Predictive Invariance across Structured Biomedical Domains Wengong Jin Regina Barzilay Tommi Jaakkola OOD 26 27 0 06 Jun 2020
Data-Driven Prediction of Embryo Implantation Probability Using IVF Time-lapse Imaging D. H. Silver M. Feder Y. Gold-Zamir A. Polsky S. Rosentraub Efrat Shachor A. Weinberger P. Mazur V. Zukin A. Bronstein 9 12 0 01 Jun 2020
Semi-Supervised Hierarchical Drug Embedding in Hyperbolic Space Ke Yu Shyam Visweswaran Kayhan Batmanghelich BDL 13 27 0 01 Jun 2020
$PaccMann$^{RL}$ on SARS-CoV-2: Designing antiviral candidates with conditional generative models$ PaccMann $^{RL}$ on SARS-CoV-2: Designing antiviral candidates with conditional generative models Jannis Born Matteo Manica Joris Cadow Greta Markert N. Mill Modestas Filipavicius María Rodríguez Martínez 29 4 0 27 May 2020
Multi-View Graph Neural Networks for Molecular Property Prediction Hehuan Ma Yatao Bian Yu Rong Wenbing Huang Tingyang Xu Wei-yang Xie Geyan Ye Junzhou Huang 21 44 0 17 May 2020
Graph Neural Networks with Composite Kernels Yufan Zhou Jiayi Xian Changyou Chen Jinhui Xu GNN 10 2 0 16 May 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 30 2,652 0 02 May 2020
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models Vijil Chenthamarakshan Payel Das Samuel C. Hoffman Hendrik Strobelt Inkit Padhi ... Benjamin Hoover Matteo Manica Jannis Born Teodoro Laino Aleksandra Mojsilović 37 41 0 02 Apr 2020
A Survey of Deep Learning for Scientific Discovery M. Raghu Erica Schmidt OOD AI4CE 38 120 0 26 Mar 2020
A comprehensive study on the prediction reliability of graph neural networks for virtual screening Soojung Yang K. Lee Seongok Ryu 19 7 0 17 Mar 2020
Meta-Learning GNN Initializations for Low-Resource Molecular Property Prediction Cuong C. Nguyen Constantine Kreatsoulas K. Branson AI4CE 14 14 0 12 Mar 2020
Directional Message Passing for Molecular Graphs Johannes Klicpera Janek Groß Stephan Günnemann 57 848 0 06 Mar 2020
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data Marc Finzi Samuel Stanton Pavel Izmailov A. Wilson 28 316 0 25 Feb 2020
Neural Message Passing on High Order Paths Daniel Flam-Shepherd Tony C Wu Pascal Friederich Alán Aspuru-Guzik GNN AI4CE 24 49 0 24 Feb 2020
Memory-Based Graph Networks Amir Hosein Khas Ahmadi Kaveh Hassani Parsa Moradi Leo Lee Q. Morris GNN 29 90 0 21 Feb 2020
Set2Graph: Learning Graphs From Sets Hadar Serviansky Nimrod Segol Jonathan Shlomi Kyle Cranmer Eilam Gross Haggai Maron Y. Lipman PINN GNN 16 35 0 20 Feb 2020
Molecule Attention Transformer Lukasz Maziarka Tomasz Danel Slawomir Mucha Krzysztof Rataj Jacek Tabor Stanislaw Jastrzebski 19 167 0 19 Feb 2020
PDDLGym: Gym Environments from PDDL Problems Tom Silver Rohan Chitnis AI4CE 25 55 0 15 Feb 2020
Predicting drug properties with parameter-free machine learning: Pareto-Optimal Embedded Modeling (POEM) Andrew E. Brereton S. MacKinnon Z. Safikhani Shawn Reeves Sana Alwash V. Shahani A. Windemuth 11 8 0 11 Feb 2020
Can Graph Neural Networks Count Substructures? Zhengdao Chen Lei Chen Soledad Villar Joan Bruna GNN 57 319 0 10 Feb 2020
Learning High Order Feature Interactions with Fine Control Kernels Hristo S. Paskov Alex Paskov Robert West 13 2 0 09 Feb 2020
Molecule Property Prediction and Classification with Graph Hypernetworks Eliya Nachmani Lior Wolf GNN 11 15 0 01 Feb 2020
Machine learning on DNA-encoded libraries: A new paradigm for hit-finding Kevin McCloskey E. Sigel S. Kearnes L. Xue Xia Tian ... C. Hupp Anthony D. Keefe Christopher J. Mulhern Ying Zhang Patrick F. Riley 51 103 0 31 Jan 2020
Machine learning and AI-based approaches for bioactive ligand discovery and GPCR-ligand recognition S. Raschka Benjamin Kaufman AI4CE 24 67 0 17 Jan 2020
Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport Tengfei Ma Jie Chen 30 24 0 24 Dec 2019
Drug-Target Indication Prediction by Integrating End-to-End Learning and Fingerprints Brighter Agyemang Wei-Ping Wu Michael Y. Kpiebaareh Ebenezer Nanor 19 2 0 03 Dec 2019
Explanatory Masks for Neural Network Interpretability Lawrence Phillips Garrett B. Goh Nathan Oken Hodas FAtt MILM AAML 13 4 0 15 Nov 2019
A Hierarchy of Graph Neural Networks Based on Learnable Local Features M. Li Meng Dong Jiawei Zhou Alexander M. Rush AI4CE GNN 33 7 0 13 Nov 2019
SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery Shion Honda Shoi Shi H. Ueda MedIm 17 172 0 12 Nov 2019
Machine learning for molecular simulation Frank Noé A. Tkatchenko K. Müller C. Clementi AI4CE 16 642 0 07 Nov 2019
Coverage Guided Testing for Recurrent Neural Networks Wei Huang Youcheng Sun Xing-E. Zhao James Sharp Wenjie Ruan Jie Meng Xiaowei Huang AAML 17 47 0 05 Nov 2019
Deep Learning for Molecular Graphs with Tiered Graph Autoencoders and Graph Prediction Daniel T. Chang AI4CE GNN 16 3 0 24 Oct 2019
ProDyn0: Inferring calponin homology domain stretching behavior using graph neural networks Ali Madani Cyna R Shirazinejad Jia Rui Ong Hengameh Shams M. Mofrad 27 0 0 22 Oct 2019
Transformer-CNN: Fast and Reliable tool for QSAR Pavel Karpov Guillaume Godin Igor V. Tetko ViT 20 11 0 21 Oct 2019
Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction Gabriele Scalia Colin A. Grambow Barbara Pernici Yi‐Pei Li W. Green BDL 17 8 0 07 Oct 2019
Oblique Decision Trees from Derivatives of ReLU Networks Guang-He Lee Tommi Jaakkola 11 23 0 30 Sep 2019
Deep Generative Model for Sparse Graphs using Text-Based Learning with Augmentation in Generative Examination Networks R. V. Deursen Guillaume Godin 19 1 0 24 Sep 2019
Learning Universal Graph Neural Network Embeddings With Aid Of Transfer Learning Saurabh Verma Zhi-Li Zhang FedML GNN SSL 20 9 0 22 Sep 2019
Spatial Graph Convolutional Networks Tomasz Danel Przemysław Spurek Jacek Tabor Marek Śmieja Lukasz Struski Agnieszka Słowik Lukasz Maziarka GNN 32 10 0 11 Sep 2019