Record link: 
http://hdl.handle.net/20.500.12708/222430
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Title: 
CGR-SMILES: A Compact and Universal Sequence Representation for Chemical Reaction Modeling
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Citation: 
Gerhaher, A. C., Sulpizio, G., Jorner, K., & Heid, E. C. (2025, December 2). CGR-SMILES: A Compact and Universal Sequence Representation for Chemical Reaction Modeling [Poster Presentation]. 20th Women in Machine Learning Workshop (WiML 2025), United States of America (the).
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Publication Type: 
Presentation - Poster Presentation
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Language: 
English
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Authors: 
Gerhaher, Anna Charlotte 
Sulpizio, Giustino 
Jorner, Kjell 
Heid, Esther Carina 
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Organisational Unit: 
E165-03-1 - Forschungsgruppe Theoretische Materialchemie 
E056-23 - Fachbereich Innovative Combinations and Applications of AI and ML (iCAIML) 
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Date (published): 
2-Dec-2025
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Event name: 
20th Women in Machine Learning Workshop (WiML 2025) 
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Event date: 
2-Dec-2025
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Event place: 
United States of America (the)
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Keywords: 
cheminformatics; ai for science; deep learning in chemistry
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Research Areas: 
Modeling and Simulation: 50%
Computational Materials Science: 50%
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Science Branch: 
1040 - Chemie: 100%
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