Papers citing Prediction of chemical reaction yields using deep learning
Completion of Partial Reaction Equations
ChemRxiv · 2020
Alain C. Vaucher, Philippe Schwaller, Teodoro Laino
Read original paper ↗ ·Completion of Partial Reaction Equations
ChemRxiv · 2020
Alain C. Vaucher, Philippe Schwaller, Teodoro Laino
Read original paper ↗ ·Data augmentation strategies to improve reaction yield predictions and estimate uncertainty
ChemRxiv · 2020
Philippe Schwaller, Alain C. Vaucher, Teodoro Laino, Jean‐Louis Reymond
Read original paper ↗ ·Data augmentation strategies to improve reaction yield predictions and estimate uncertainty
ChemRxiv · 2020
Philippe Schwaller, Alain C. Vaucher, Teodoro Laino, Jean‐Louis Reymond
Read original paper ↗ ·Chemical data intelligence for sustainable chemistry
Chemical Society Reviews · 2021
Jana M. Weber, Zhen Guo, Chonghuan Zhang, Artur M. Schweidtmann, Alexei A. Lapkin
Read original paper ↗ ·DeepReac+: deep active learning for quantitative modeling of organic chemical reactions
Chemical Science · 2021
Yukang Gong, Dongyu Xue, Guohui Chuai, Jing Yu, Qi Liu
Read original paper ↗ ·Toward Machine Learning-Enhanced High-Throughput Experimentation
Trends in Chemistry · 2021
Natalie S. Eyke, Brent A. Koscher, Klavs F. Jensen
Read original paper ↗ ·Transformative Applications of Machine Learning for Chemical Reactions
arXiv (Cornell University) · 2021
Markus Meuwly
Read original paper ↗ ·Mapping the space of chemical reactions using attention-based neural networks
Nature Machine Intelligence · 2021
Philippe Schwaller, Daniel Probst, Alain C. Vaucher, Vishnu H Nair, David Kreutter, Teodoro Laino, Jean‐Louis Reymond
Read original paper ↗ ·Organic reactivity from mechanism to machine learning
Nature Reviews Chemistry · 2021
Kjell Jorner, Anna Tomberg, Christoph Alexander Bauer, Christian Sköld, Per‐Ola Norrby
Read original paper ↗ ·ExtractionScore: A Quantitative Framework for Evaluating Synthetic Routes on Predicted Liquid–Liquid Extraction Performance
Journal of Chemical Information and Modeling · 2021
Anatoliy Kuznetsov, Nikolaos V. Sahinidis
Read original paper ↗ ·Graph Neural Networks for Predicting Chemical Reaction Performance
ChemRxiv · 2021
Mandana Saebi, Bozhao Nan, John E. Herr, Jessica Wahlers, Olaf Wiest, Nitesh V. Chawla
Read original paper ↗ ·Machine Learning for Chemical Reactions
Chemical Reviews · 2021
Markus Meuwly
Read original paper ↗ ·Evaluating the Performance of a Transformer-based Organic Reaction Prediction Model
ChemRxiv · 2021
William Borrelli, Joshua Schrier
Read original paper ↗ ·Reusability report: Learning the language of synthetic methods used in medicinal chemistry
Nature Machine Intelligence · 2021
Jon Paul Janet, Anna Tomberg, Jonas Boström
Read original paper ↗ ·Reaction Classification and Yield Prediction using the Differential Reaction Fingerprint DRFP
Venue not supplied by source · 2021
Daniel Probst, Philippe Schwaller, Jean‐Louis Reymond
Read original paper ↗ ·Machine Learning Force Fields: Recent Advances and Remaining Challenges
The Journal of Physical Chemistry Letters · 2021
Igor Poltavsky, Alexandre Tkatchenko
Read original paper ↗ ·3D Computer Vision Models Predict DFT-Level HOMO-LUMO Gap Energies from Force-Field-Optimized Geometries
ChemRxiv · 2021
Michael Maser, Sarah E. Reisman
Read original paper ↗ ·Prediction of Multicomponent Reaction Yields Using Machine Learning
Chinese Journal of Chemistry · 2021
Xingyong Zhu, Chuan‐Kun Ran, Ming Fen Wen, Gui‐Ling Guo, Yuan Liu, Li‐Li Liao, Yi‐Zhou Li, Meng‐Long Li, Da‐Gang Yu
Read original paper ↗ ·How AI for Synthesis Can Help Tackle Challenges in Molecular Discovery
CHIMIA International Journal for Chemistry · 2021
Amol Thakkar, Philippe Schwaller
Read original paper ↗ ·National Institutes of Health (NIH) Workshop on Reaction Informatics
ChemRxiv · 2021
Wendy A. Warr
Read original paper ↗ ·Reaction Data Curation I: Chemical Structures and Transformations Standardization
Molecular Informatics · 2021
Timur Rustemovich Gimadiev, Arkadii Lin, Valentina A. Afonina, Dinar Batyrshin, Нугманов Рамиль Ирекович, Tagir N. Akhmetshin, Pavel Sidorov, Natalia Duybankova, Jonas Verhoeven, Jörg K. Wegner, Hugo Ceulemans, Andrey Gedich, Timur Madzhidov, Alexandre A. Varnek
Read original paper ↗ ·Highly accurate prediction of reaction performance and enantioselectivity with a uniform machine learning protocol
Research Square · 2021
Xiaofei Sun, Jingyuan Zhu, Hengzhi You, Bin Chen, Fen‐Er Chen
Read original paper ↗ ·IMG2SMI: Translating Molecular Structure Images to Simplified Molecular-input Line-entry System
arXiv (Cornell University) · 2021
Campos, Daniel, Heng Ji
Read original paper ↗ ·Prediction of Reaction Yield for Buchwald‐Hartwig Cross‐coupling Reactions Using Deep Learning
Molecular Informatics · 2021
Akinori Sato, Tomoyuki Miyao, Kimito Funatsu
Read original paper ↗ ·Reactions’ Descriptors Selection and Yield Estimation Using Metaheuristic Algorithms and Voting Ensemble
Computers, materials & continua/Computers, materials & continua (Print) · 2021
Olutomilayo Olayemi Petinrin, Faisal Saeed, Xiangtao Li, Fahad Mahmoud Ghabban, Ka‐Chun Wong
Read original paper ↗ ·The Evolution of Data-Driven Modeling in Organic Chemistry
ACS Central Science · 2021
Wendy L. Williams, Lingyu Zeng, Tobias Gensch, Matthew S. Sigman, Abigail G. Doyle, Eric V. Anslyn
Read original paper ↗ ·Automated Exploration of Prebiotic Chemical Reaction Space: Progress and Perspectives
Life · 2021
Siddhant Sharma, Aayush Arya, Rómulo Cruz-Simbrón, Henderson James Cleaves
Read original paper ↗ ·Machine learning modelling of chemical reaction characteristics: yesterday, today, tomorrow
Mendeleev Communications · 2021
Timur Madzhidov, Assima Rakhimbekova, Valentina A. Afonina, Timur Rustemovich Gimadiev, Ravil N. Mukhametgaleev, Нугманов Рамиль Ирекович, Igor I. Baskin, Alexandre A. Varnek
Read original paper ↗ ·Applications of Artificial Intelligence in Drug Design: Opportunities and Challenges
Methods in molecular biology · 2021
Morgan C. Thomas, Andrew Boardman, Miguel García-Ortegón, Hongbin Yang, Chris de Graaf, Andreas Bender
Read original paper ↗ ·Machine Learning of Reaction Properties via Learned Representations of the Condensed Graph of Reaction
Journal of Chemical Information and Modeling · 2021
Esther Heid, William H. Green
Read original paper ↗ ·Discovering New Chemistry with an Autonomous Robotic Platform Driven by a Reactivity-Seeking Neural Network
ACS Central Science · 2021
Dario Caramelli, Jarosław M. Granda, S. Hessam M. Mehr, Dario Cambié, Alon Henson, Leroy Cronin
Read original paper ↗ ·Progress towards machine learning reaction rate constants
Physical Chemistry Chemical Physics · 2021
Evan Komp, Nida Janulaitis, Stéphanie Valleau
Read original paper ↗ ·Geometric deep learning on molecular representations
Nature Machine Intelligence · 2021
Kenneth Atz, Francesca Grisoni, Gisbert Schneider
Read original paper ↗ ·Low-cost prediction of molecular and transition state partition functions via machine learning
Chemical Science · 2022
Evan Komp, Stéphanie Valleau
Read original paper ↗ ·Predicting reaction conditions from limited data through active transfer learning
Chemical Science · 2022
Eunjae Shim, Joshua A. Kammeraad, Ziping Xu, Ambuj Tewari, Tim Cernak, Paul M. Zimmerman
Read original paper ↗ ·Reaction classification and yield prediction using the differential reaction fingerprint DRFP
Digital Discovery · 2022
Daniel Probst, Philippe Schwaller, Jean‐Louis Reymond
Read original paper ↗ ·Routescore: Punching the Ticket to More Efficient Materials Development
ACS Central Science · 2022
Martin T. Seifrid, Riley J. Hickman, Andrés Aguilar‐Granda, Cyrille Lavigne, Jenya Vestfrid, Tony Wu, Théophile Gaudin, Emily J. Hopkins, Alán Aspuru‐Guzik
Read original paper ↗ ·Generalizing Performance Equations in Heterogeneous Catalysis from Hybrid Data and Statistical Learning
ACS Catalysis · 2022
Sergio Pablo‐García, Albert Sabadell‐Rendón, Ali J. Saadun, Santiago Morandi, Javier Pérez‐Ramírez, Núria López
Read original paper ↗ ·Quantum Mechanics and Machine Learning Synergies: Graph Attention Neural Networks to Predict Chemical Reactivity
Journal of Chemical Information and Modeling · 2022
Mohammadamin Tavakoli, Aaron D. Mood, David L. Van Vranken, Pierre Baldi
Read original paper ↗ ·Regression Transformer enables concurrent sequence regression and generation for molecular language modelling
arXiv (Cornell University) · 2022
Jannis Born, Matteo Manica
Read original paper ↗ ·X-MOL: large-scale pre-training for molecular understanding and diverse molecular analysis
中国科学通报：英文版 · 2022
Dongyu Xue, Han Zhang, Xiaohan Chen, Dongling Xiao, Yukang Gong, Guohui Chuai, Yu Sun, Hao Tian, Hua Ren Wu, Yukun Li, Qi Liu
Read original paper ↗ ·Quantum chemistry-augmented neural networks for reactivity prediction: Performance, generalizability, and explainability
The Journal of Chemical Physics · 2022
Thijs Stuyver, Connor W. Coley
Read original paper ↗ ·Application of machine learning for advanced material prediction and design
EcoMat · 2022
Cheuk Hei Chan, Mingzi Sun, Bolong Huang
Read original paper ↗ ·Machine intelligence for chemical reaction space
Wiley Interdisciplinary Reviews Computational Molecular Science · 2022
Philippe Schwaller, Alain C. Vaucher, Rubén Laplaza, Charlotte Bunne, Andreas Krause, Clémence Corminbœuf, Teodoro Laino
Read original paper ↗ ·Machine Learning May Sometimes Simply Capture Literature Popularity Trends: A Case Study of Heterocyclic Suzuki–Miyaura Coupling
Journal of the American Chemical Society · 2022
Wiktor Beker, Rafał Roszak, Agnieszka Wołos, Nicholas H. Angello, Vandana Rathore, Martin D. Burke, Bartosz A. Grzybowski
Read original paper ↗ ·Process Mining and Deep Neural Network approach for the Prediction of Business Process Outcome
International Conference on Communication, Computing and Internet of Things (IC3IoT) · 2022
B Kamala, B. Latha
Read original paper ↗ ·Unified Deep Learning Model for Multitask Reaction Predictions with Explanation
Journal of Chemical Information and Modeling · 2022
Jieyu Lü, Yingkai Zhang
Read original paper ↗ ·Accurate, affordable, and generalizable machine learning simulations of transition metal x-ray absorption spectra using the XANESNET deep neural network
The Journal of Chemical Physics · 2022
Conor D. Rankine, Thomas J. Penfold
Read original paper ↗ ·Software tools for green and sustainable chemistry
Current Opinion in Green and Sustainable Chemistry · 2022
Ivan N. Derbenev, James Dowden, Jamie Twycross, Jonathan D. Hirst
Read original paper ↗ ·