Deep learning for molecular design - a review of the state of the art

11 March 2019

Papers citing "Deep learning for molecular design - a review of the state of the art"

35 / 35 papers shown

Title
Multi-Constraint Molecular Generation using Sparsely Labelled Training Data for Localized High-Concentration Electrolyte Diluent Screening J. Mailoa Xin Li J. Qiu Shengyu Zhang 17 0 0 12 Jan 2023
De novo PROTAC design using graph-based deep generative models Divya Nori Connor W. Coley Rocío Mercado 19 9 0 04 Nov 2022
Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES E. Bjerrum Christian Margreitter Thomas Blaschke Raquel Lopez-Rios de Castro 37 11 0 22 Oct 2022
Topology-Driven Generative Completion of Lacunae in Molecular Data Dmitry Zubarev Petar Ristoski 23 0 0 29 Jul 2022
Controllable Data Generation by Deep Learning: A Review Shiyu Wang Yuanqi Du Xiaojie Guo Bo Pan Zhaohui Qin Liang Zhao 31 28 0 19 Jul 2022
An Unpooling Layer for Graph Generation Yi Guo Dongmian Zou Gilad Lerman 16 2 0 04 Jun 2022
Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning Jiace Sun Lixue Cheng Thomas F. Miller 27 2 0 31 May 2022
Transferring Chemical and Energetic Knowledge Between Molecular Systems with Machine Learning Sajjad Heydari S. Raniolo L. Livi V. Limongelli 15 2 0 06 May 2022
Self-focusing virtual screening with active design space pruning David E. Graff Matteo Aldeghi Joseph A. Morrone K. E. Jordan Edward O. Pyzer-Knapp Connor W. Coley 29 24 0 03 May 2022
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design Yuanqi Du Tianfan Fu Jimeng Sun Shengchao Liu AI4CE 31 86 0 28 Mar 2022
AugLiChem: Data Augmentation Library of Chemical Structures for Machine Learning Rishikesh Magar Yuyang Wang Cooper Lorsung Chen Liang Hariharan Ramasubramanian Peiyuan Li A. Farimani 28 27 0 30 Nov 2021
Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations Keir Adams L. Pattanaik Connor W. Coley 21 32 0 08 Oct 2021
Inverse design of 3d molecular structures with conditional generative neural networks Niklas W. A. Gebauer M. Gastegger Stefaan S. P. Hessmann Klaus-Robert Muller Kristof T. Schütt AI4CE 192 166 0 10 Sep 2021
Evaluating the progress of Deep Reinforcement Learning in the real world: aligning domain-agnostic and domain-specific research J. Luis E. Crawley B. Cameron OffRL 25 6 0 07 Jul 2021
Artificial Intelligence in Drug Discovery: Applications and Techniques Jianyuan Deng Zhibo Yang Iwao Ojima Dimitris Samaras Fusheng Wang AI4TS 26 100 0 09 Jun 2021
Applying Deutsch's concept of good explanations to artificial intelligence and neuroscience -- an initial exploration Daniel C. Elton 18 4 0 16 Dec 2020
AI Discovering a Coordinate System of Chemical Elements: Dual Representation by Variational Autoencoders A. Glushkovsky DRL 19 6 0 24 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
Scaffold-constrained molecular generation Maxime Langevin H. Minoux M. Levesque M. Bianciotto 26 45 0 15 Sep 2020
Physics-Informed Neural Networks for Nonhomogeneous Material Identification in Elasticity Imaging Enrui Zhang Minglang Yin George Karniadakis 12 64 0 02 Sep 2020
Machine learning for electronically excited states of molecules Julia Westermayr P. Marquetand 17 257 0 10 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
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
CRYSPNet: Crystal Structure Predictions via Neural Network Haotong Liang V. Stanev A. Kusne Ichiro Takeuchi 19 37 0 31 Mar 2020
Autonomous discovery in the chemical sciences part II: Outlook Connor W. Coley Natalie S. Eyke K. Jensen 29 171 0 30 Mar 2020
A deep-learning view of chemical space designed to facilitate drug discovery P. Maragakis Hunter M. Nisonoff B. Cole D. Shaw 34 28 0 07 Feb 2020
Generative adversarial networks (GAN) based efficient sampling of chemical space for inverse design of inorganic materials Yabo Dan Yong Zhao Xiang Li Shaobo Li Ming Hu Jianjun Hu AI4CE GAN 27 192 0 12 Nov 2019
Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular string representation Mario Krenn Florian Hase AkshatKumar Nigam Pascal Friederich Alán Aspuru-Guzik 11 70 0 31 May 2019
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models Daniil Polykovskiy Alexander Zhebrak Benjamín Sánchez-Lengeling Sergey Golovanov Oktai Tatanov ... Simon Johansson Hongming Chen Sergey I. Nikolenko Alán Aspuru-Guzik Alex Zhavoronkov ELM 197 633 0 29 Nov 2018
Independent Vector Analysis for Data Fusion Prior to Molecular Property Prediction with Machine Learning Zois Boukouvalas Daniel C. Elton Peter W. Chung M. Fuge 25 9 0 01 Nov 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 206 885 0 07 Jun 2018
Conditional molecular design with deep generative models Seokho Kang Kyunghyun Cho BDL 166 183 0 30 Apr 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 224 1,340 0 12 Feb 2018
Constrained Bayesian Optimization for Automatic Chemical Design Ryan-Rhys Griffiths José Miguel Hernández-Lobato BDL 39 76 0 16 Sep 2017
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,636 0 03 Jul 2012