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
GEOM: Energy-annotated molecular conformations for property prediction and molecular generation Simon Axelrod Rafael Gómez-Bombarelli 3DV AI4CE 31 206 0 09 Jun 2020
Population-Based Black-Box Optimization for Biological Sequence Design Christof Angermüller David Belanger Andreea Gane Zelda E. Mariet David Dohan Kevin Patrick Murphy Lucy J. Colwell D. Sculley 21 133 0 05 Jun 2020
Semi-Supervised Hierarchical Drug Embedding in Hyperbolic Space Ke Yu Shyam Visweswaran Kayhan Batmanghelich BDL 19 27 0 01 Jun 2020
Semi-supervised Embedding Learning for High-dimensional Bayesian Optimization Jingfan Chen Guanghui Zhu Chun Yuan Yihua Huang 9 15 0 29 May 2020
The prospects of quantum computing in computational molecular biology C. Outeiral M. Strahm Jiye Shi Garrett M. Morris S. Benjamin Charlotte M. Deane 45 177 0 26 May 2020
Fast differentiable DNA and protein sequence optimization for molecular design Johannes Linder Georg Seelig 28 54 0 22 May 2020
Deep Learning and Knowledge-Based Methods for Computer Aided Molecular Design -- Toward a Unified Approach: State-of-the-Art and Future Directions Abdulelah S. Alshehri R. Gani Fengqi You AI4CE 30 83 0 18 May 2020
Variational Hyper-Encoding Networks Phuoc Nguyen T. Tran Sunil R. Gupta Santu Rana H. Dam Svetha Venkatesh BDL DRL 12 2 0 18 May 2020
An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties Zekun Ren S. Tian Juhwan Noh Felipe Oviedo G. Xing ... Qianxiao Li Senthilnath Jayavelu K. Hippalgaonkar Yousung Jung Tonio Buonassisi AI4CE 40 130 0 15 May 2020
Preventing Posterior Collapse with Levenshtein Variational Autoencoder Serhii Havrylov Ivan Titov DRL 9 19 0 30 Apr 2020
Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning S. Gottipati B. Sattarov Sufeng Niu Yashaswi Pathak Haoran Wei ... Simon R. Blackburn Connor W. Coley Jian Tang Sarath Chandar Yoshua Bengio 14 108 0 26 Apr 2020
On the Compressive Power of Boolean Threshold Autoencoders A. Melkman Sini Guo W. Ching Pengyu Liu Tatsuya Akutsu AI4CE 16 3 0 21 Apr 2020
Continuous Representation of Molecules Using Graph Variational Autoencoder Mohammadamin Tavakoli Pierre Baldi BDL GNN DRL 11 9 0 17 Apr 2020
The general theory of permutation equivarant neural networks and higher order graph variational encoders Erik H. Thiede Truong-Son Hy Risi Kondor 32 35 0 08 Apr 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
Autonomous discovery in the chemical sciences part II: Outlook Connor W. Coley Natalie S. Eyke K. Jensen 29 171 0 30 Mar 2020
Autonomous discovery in the chemical sciences part I: Progress Connor W. Coley Natalie S. Eyke K. Jensen 26 213 0 30 Mar 2020
Interval Neural Networks as Instability Detectors for Image Reconstructions Jan Macdonald M. März Luis Oala Wojciech Samek 28 2 0 27 Mar 2020
Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge Florian Hase Matteo Aldeghi Riley J. Hickman L. Roch Alán Aspuru-Guzik 47 105 0 26 Mar 2020
Inverse Design of Potential Singlet Fission Molecules using a Transfer Learning Based Approach Akshay Subramanian Utkarsh Saha Tejasvini Sharma N. Tailor S. Satapathi 19 1 0 17 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
Deterministic Decoding for Discrete Data in Variational Autoencoders Daniil Polykovskiy Dmitry Vetrov OffRL 21 8 0 04 Mar 2020
Permutation Invariant Graph Generation via Score-Based Generative Modeling Chenhao Niu Yang Song Jiaming Song Shengjia Zhao Aditya Grover Stefano Ermon DiffM 34 260 0 02 Mar 2020
ML4Chem: A Machine Learning Package for Chemistry and Materials Science Muammar El Khatib W. A. Jong VLM 18 6 0 02 Mar 2020
A Deep Generative Model for Fragment-Based Molecule Generation Marco Podda D. Bacciu Alessio Micheli VLM BDL 12 51 0 28 Feb 2020
PaDGAN: A Generative Adversarial Network for Performance Augmented Diverse Designs Wei Chen Faez Ahmed 11 11 0 26 Feb 2020
Computer-inspired Quantum Experiments Mario Krenn Manuel Erhard A. Zeilinger 27 73 0 23 Feb 2020
ChemGrapher: Optical Graph Recognition of Chemical Compounds by Deep Learning M. Oldenhof Adam Arany Yves Moreau Jaak Simm GNN 29 51 0 23 Feb 2020
Molecule Attention Transformer Lukasz Maziarka Tomasz Danel Slawomir Mucha Krzysztof Rataj Jacek Tabor Stanislaw Jastrzebski 19 167 0 19 Feb 2020
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics G. Simm Robert Pinsler José Miguel Hernández-Lobato AI4CE 21 82 0 18 Feb 2020
The Synthesizability of Molecules Proposed by Generative Models Wenhao Gao Connor W. Coley 19 251 0 17 Feb 2020
Graph Deconvolutional Generation Daniel Flam-Shepherd Tony C Wu Alán Aspuru-Guzik BDL 28 31 0 14 Feb 2020
Improving Molecular Design by Stochastic Iterative Target Augmentation Kevin Kaichuang Yang Wengong Jin Kyle Swanson Regina Barzilay Tommi Jaakkola 30 26 0 11 Feb 2020
Black-Box Optimization with Local Generative Surrogates S. Shirobokov V. Belavin Michael Kagan Andrey Ustyuzhanin A. G. Baydin 8 3 0 11 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 21 8 0 11 Feb 2020
Exploring Chemical Space using Natural Language Processing Methodologies for Drug Discovery Hakime Öztürk Arzucan Özgür P. Schwaller Teodoro Laino Elif Özkirimli 30 116 0 10 Feb 2020
Multi-Objective Molecule Generation using Interpretable Substructures Wengong Jin Regina Barzilay Tommi Jaakkola 19 23 0 08 Feb 2020
Hierarchical Generation of Molecular Graphs using Structural Motifs Wengong Jin Regina Barzilay Tommi Jaakkola 21 279 0 08 Feb 2020
A deep-learning view of chemical space designed to facilitate drug discovery P. Maragakis Hunter M. Nisonoff B. Cole D. Shaw 38 28 0 07 Feb 2020
Inverse Learning of Symmetries Mario Wieser S. Parbhoo Aleksander Wieczorek Volker Roth 13 6 0 07 Feb 2020
Learning Extremal Representations with Deep Archetypal Analysis S. Keller M. Samarin Fabricio Arend Torres Mario Wieser Volker Roth 12 22 0 03 Feb 2020
Edge-based sequential graph generation with recurrent neural networks D. Bacciu Alessio Micheli Marco Podda GNN 16 34 0 31 Jan 2020
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization Benjamin Letham Roberto Calandra Akshara Rai E. Bakshy 75 110 0 31 Jan 2020
Discovery of Self-Assembling $π$ -Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation Kirill Shmilovich R. Mansbach Hythem Sidky Olivia E. Dunne S. Panda J. Tovar Andrew L. Ferguson 28 76 0 27 Jan 2020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation Chence Shi Minkai Xu Zhaocheng Zhu Weinan Zhang Ming Zhang Jian Tang 64 426 0 26 Jan 2020
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning Kevin Maik Jablonka D. Ongari S. M. Moosavi B. Smit AI4CE 31 350 0 18 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
High-Fidelity Synthesis with Disentangled Representation Wonkwang Lee Donggyun Kim Seunghoon Hong Honglak Lee DRL 16 66 0 13 Jan 2020
Model Inversion Networks for Model-Based Optimization Aviral Kumar Sergey Levine OffRL 33 93 0 31 Dec 2019
Black Box Recursive Translations for Molecular Optimization Farhan N. Damani Vishnu Sresht Stephen Ra 24 5 0 21 Dec 2019