Automatic chemical design using a data-driven continuous representation of molecules

7 October 2016

Rafael Gómez-Bombarelli

Jennifer N. Wei

David Duvenaud

José Miguel Hernández-Lobato

Benjamín Sánchez-Lengeling

Dennis Sheberla

J. Aguilera-Iparraguirre

Papers citing "Automatic chemical design using a data-driven continuous representation of molecules"

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Title
Optimizing Molecules using Efficient Queries from Property Evaluations Samuel C. Hoffman Vijil Chenthamarakshan Kahini Wadhawan Pin-Yu Chen Payel Das 41 69 0 03 Nov 2020
Polymer Informatics: Current Status and Critical Next Steps Lihua Chen G. Pilania Rohit Batra T. D. Huan Chiho Kim Christopher Kuenneth R. Ramprasad AI4CE 20 177 0 01 Nov 2020
Goal directed molecule generation using Monte Carlo Tree Search Anand A. Rajasekar Karthik Raman Balaraman Ravindran 14 6 0 30 Oct 2020
Controlled Molecule Generator for Optimizing Multiple Chemical Properties Bonggun Shin Sungsoo Park Jinyeong Bak Joyce C. Ho 33 15 0 26 Oct 2020
Robust Disentanglement of a Few Factors at a Time Benjamin Estermann Markus Marks M. Yanik CoGe OOD DRL 8 3 0 26 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
Learning Latent Space Energy-Based Prior Model for Molecule Generation Bo Pang Tian Han Ying Nian Wu 12 10 0 19 Oct 2020
Learning a Continuous Representation of 3D Molecular Structures with Deep Generative Models Matthew Ragoza Tomohide Masuda D. Koes DiffM MedIm 75 31 0 17 Oct 2020
Generating 3D Molecular Structures Conditional on a Receptor Binding Site with Deep Generative Models Tomohide Masuda Matthew Ragoza D. Koes DiffM 37 52 0 16 Oct 2020
3DMolNet: A Generative Network for Molecular Structures V. Nesterov Mario Wieser Volker Roth AI4CE 173 33 0 08 Oct 2020
Maximum Reward Formulation In Reinforcement Learning S. Gottipati Yashaswi Pathak Rohan Nuttall Sahir Raviteja Chunduru Ahmed Touati Sriram Ganapathi Subramanian Matthew E. Taylor Sarath Chandar 26 13 0 08 Oct 2020
MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization Tianfan Fu Cao Xiao Xinhao Li Lucas Glass Jimeng Sun 27 75 0 05 Oct 2020
Goal-directed Generation of Discrete Structures with Conditional Generative Models Amina Mollaysa Brooks Paige Alexandros Kalousis 37 8 0 05 Oct 2020
A primer on model-guided exploration of fitness landscapes for biological sequence design Sam Sinai Eric D. Kelsic 45 28 0 04 Oct 2020
Gaussian Process Molecule Property Prediction with FlowMO Henry B. Moss Ryan-Rhys Griffiths 21 23 0 02 Oct 2020
BOSS: Bayesian Optimization over String Spaces Henry B. Moss Daniel Beck Javier I. González David S. Leslie Paul Rayson 11 68 0 02 Oct 2020
ChemoVerse: Manifold traversal of latent spaces for novel molecule discovery Harshdeep Singh Nicholas McCarthy Q. Ain Jeremiah Hayes 25 3 0 29 Sep 2020
Physics-Constrained Predictive Molecular Latent Space Discovery with Graph Scattering Variational Autoencoder Navid Shervani-Tabar N. Zabaras BDL DRL 13 3 0 29 Sep 2020
Benchmarking deep inverse models over time, and the neural-adjoint method Simiao Ren Willie J. Padilla Jordan M. Malof BDL PINN 14 41 0 27 Sep 2020
Chemical Property Prediction Under Experimental Biases Yang Liu H. Kashima AI4CE 33 1 0 18 Sep 2020
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 34 79 0 17 Sep 2020
Generate Novel Molecules With Target Properties Using Conditional Generative Models Abhinav Sagar 31 0 0 15 Sep 2020
Scaffold-constrained molecular generation Maxime Langevin H. Minoux M. Levesque M. Bianciotto 26 46 0 15 Sep 2020
Iterative Refinement in the Continuous Space for Non-Autoregressive Neural Machine Translation Jason D. Lee Raphael Shu Kyunghyun Cho 6 26 0 15 Sep 2020
Conditional Constrained Graph Variational Autoencoders for Molecule Design Davide Rigoni Nicoló Navarin A. Sperduti BDL 19 18 0 01 Sep 2020
A Systematic Assessment of Deep Learning Models for Molecule Generation Davide Rigoni Nicoló Navarin A. Sperduti 17 6 0 20 Aug 2020
Generative chemistry: drug discovery with deep learning generative models Yuemin Bian X. Xie AI4CE 11 93 0 20 Aug 2020
Scalable Combinatorial Bayesian Optimization with Tractable Statistical models Aryan Deshwal Syrine Belakaria J. Doppa 14 13 0 18 Aug 2020
Graph Polish: A Novel Graph Generation Paradigm for Molecular Optimization Chaojie Ji Yijia Zheng Ruxin Wang Yunpeng Cai Hongyan Wu 26 18 0 14 Aug 2020
Efficient Generation of Structured Objects with Constrained Adversarial Networks Luca Di Liello Pierfrancesco Ardino Jacopo Gobbi Paolo Morettin Stefano Teso Andrea Passerini GAN 27 31 0 26 Jul 2020
Privacy-preserving Artificial Intelligence Techniques in Biomedicine Reihaneh Torkzadehmahani Reza Nasirigerdeh David B. Blumenthal T. Kacprowski M. List ... Harald H. H. W. Schmidt A. Schwalber Christof Tschohl Andrea Wohner Jan Baumbach 21 60 0 22 Jul 2020
Visualizing Deep Graph Generative Models for Drug Discovery Karan Yang Chengxi Zang Fei Wang GNN 17 0 0 20 Jul 2020
A Hierarchical Approach to Scaling Batch Active Search Over Structured Data Vivek Myers Peyton Greenside 21 1 0 20 Jul 2020
SketchGraphs: A Large-Scale Dataset for Modeling Relational Geometry in Computer-Aided Design Ari Seff Yaniv Ovadia Wenda Zhou Ryan P. Adams AI4CE 3DV 21 68 0 16 Jul 2020
A Survey on Applications of Artificial Intelligence in Fighting Against COVID-19 Jianguo Chen KenLi Li Zhaolei Zhang Keqin Li Philip S. Yu 35 101 0 04 Jul 2020
Guiding Deep Molecular Optimization with Genetic Exploration Sungsoo Ahn Junsup Kim Hankook Lee Jinwoo Shin 29 70 0 04 Jul 2020
Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic Systems Mayalen Etcheverry Clément Moulin-Frier Pierre-Yves Oudeyer 9 23 0 02 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
Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits Mikolaj Sacha Mikolaj Blaz Piotr Byrski Paweł Dąbrowski-Tumański Mikołaj Chromiński Rafał Loska Pawel Wlodarczyk-Pruszynski Stanislaw Jastrzebski GNN 30 142 0 27 Jun 2020
Graph Neural Network Based Coarse-Grained Mapping Prediction Zhiheng Li Geemi P Wellawatte M. Chakraborty Heta A. Gandhi Chenliang Xu A. White AI4CE 19 32 0 24 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
We Should at Least Be Able to Design Molecules That Dock Well Tobiasz Ciepliński Tomasz Danel Sabina Podlewska Stanislaw Jastrzebski 19 29 0 20 Jun 2020
Neural Program Synthesis with a Differentiable Fixer Matej Balog Rishabh Singh Petros Maniatis Charles Sutton 14 5 0 19 Jun 2020
Practical Massively Parallel Monte-Carlo Tree Search Applied to Molecular Design Xiufeng Yang T. Aasawat Kazuki Yoshizoe 30 0 0 18 Jun 2020
MoFlow: An Invertible Flow Model for Generating Molecular Graphs Chengxi Zang Fei Wang BDL 28 280 0 17 Jun 2020
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Giorgos Bouritsas Fabrizio Frasca S. Zafeiriou M. Bronstein 58 424 0 16 Jun 2020
Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining Austin Tripp Erik A. Daxberger José Miguel Hernández-Lobato MedIm 24 135 0 16 Jun 2020
Minimum Width for Universal Approximation Sejun Park Chulhee Yun Jaeho Lee Jinwoo Shin 33 122 0 16 Jun 2020
$Data-driven determination of the spin Hamiltonian parameters and their uncertainties: The case of the zigzag-chain compound KCu$_4$P$_3$O$_{12}$$ Data-driven determination of the spin Hamiltonian parameters and their uncertainties: The case of the zigzag-chain compound KCu $_4$ P $_3$ O $_{12}$ R. Tamura K. Hukushima A. Matsuo K. Kindo M. Hase 13 1 0 13 Jun 2020
Learning the Travelling Salesperson Problem Requires Rethinking Generalization Chaitanya K. Joshi Quentin Cappart Louis-Martin Rousseau T. Laurent 21 108 0 12 Jun 2020