Learning to Plan Chemical Syntheses

14 August 2017

Papers citing "Learning to Plan Chemical Syntheses"

24 / 74 papers shown

Title
A comprehensive study on the prediction reliability of graph neural networks for virtual screening Soojung Yang K. Lee Seongok Ryu 21 7 0 17 Mar 2020
A Bayesian algorithm for retrosynthesis Zhongliang Guo Stephen Wu Mitsuru Ohno Ryo Yoshida BDL 43 27 0 06 Mar 2020
State-of-the-Art Augmented NLP Transformer models for direct and single-step retrosynthesis Igor V. Tetko Pavel Karpov R. V. Deursen Guillaume Godin 19 6 0 05 Mar 2020
From Chess and Atari to StarCraft and Beyond: How Game AI is Driving the World of AI S. Risi Mike Preuss 29 56 0 24 Feb 2020
A deep-learning view of chemical space designed to facilitate drug discovery P. Maragakis Hunter M. Nisonoff B. Cole D. Shaw 46 28 0 07 Feb 2020
Retrosynthesis Prediction with Conditional Graph Logic Network H. Dai Chengtao Li Connor W. Coley Bo Dai Le Song 26 177 0 06 Jan 2020
Combining Q-Learning and Search with Amortized Value Estimates Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez Tobias Pfaff T. Weber Lars Buesing Peter W. Battaglia OffRL 27 47 0 05 Dec 2019
DeepAtom: A Framework for Protein-Ligand Binding Affinity Prediction Yanjun Li M. Rezaei Chenglong Li Xiaolin Li D. Wu 3DV 24 61 0 01 Dec 2019
Opportunities for artificial intelligence in advancing precision medicine F. Filipp LM&MA AI4CE 19 51 0 17 Nov 2019
Predicting retrosynthetic pathways using a combined linguistic model and hyper-graph exploration strategy P. Schwaller Riccardo Petraglia Valerio Zullo Vishnu H. Nair Rico Häuselmann Riccardo Pisoni C. Bekas A. Iuliano Teodoro Laino 14 17 0 17 Oct 2019
SMILES-X: autonomous molecular compounds characterization for small datasets without descriptors G. Lambard Ekaterina Gracheva 27 20 0 20 Jun 2019
ImJoy: an open-source computational platform for the deep learning era Ouyang Wei F. Mueller Martin Hjelmare E. Lundberg C. Zimmer VLM AI4CE 14 116 0 30 May 2019
The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures Sheshera Mysore Z. Jensen Edward J. Kim Kevin Huang Haw-Shiuan Chang Emma Strubell Jeffrey Flanigan Andrew McCallum E. Olivetti 27 95 0 16 May 2019
A Universal Density Matrix Functional from Molecular Orbital-Based Machine Learning: Transferability across Organic Molecules Lixue Cheng Matthew Welborn Anders S. Christensen Thomas F. Miller 24 93 0 10 Jan 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 206 633 0 29 Nov 2018
Three-Dimensionally Embedded Graph Convolutional Network (3DGCN) for Molecule Interpretation Hyeoncheol Cho I. Choi 30 55 0 24 Nov 2018
GuacaMol: Benchmarking Models for De Novo Molecular Design Nathan Brown Marco Fiscato Marwin H. S. Segler Alain C. Vaucher ELM 44 693 0 22 Nov 2018
Learning to Predict the Cosmological Structure Formation Siyu He Yin Li Yu Feng S. Ho Siamak Ravanbakhsh Wei Chen Barnabás Póczós 22 168 0 15 Nov 2018
Molecular Transformer - A Model for Uncertainty-Calibrated Chemical Reaction Prediction P. Schwaller Teodoro Laino John McGuinness A. Horváth Constantine Bekas A. Lee 36 719 0 06 Nov 2018
Compressing physical properties of atomic species for improving predictive chemistry John E. Herr Kevin J Koh Kun Yao John A. Parkhill AI4CE 30 20 0 31 Oct 2018
Latent Molecular Optimization for Targeted Therapeutic Design Tristan Aumentado-Armstrong 15 41 0 05 Sep 2018
MolGAN: An implicit generative model for small molecular graphs Nicola De Cao Thomas Kipf GNN GAN 35 907 0 30 May 2018
A Generative Model for Inverse Design of Metamaterials Zhaocheng Liu Dayu Zhu S. Rodrigues Kyu-Tae Lee W. Cai 26 520 0 25 May 2018
A Generative Model For Electron Paths John Bradshaw Matt J. Kusner Brooks Paige Marwin H. S. Segler José Miguel Hernández-Lobato 22 55 0 23 May 2018