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Philippe Schwaller

Showing results (11-20 of 56) with videos related to

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Chimia|December 30, 2019
Data-driven Chemical Reaction Prediction and RetrosynthesisVishnu H Nair, Philippe Schwaller, Teodoro Laino
Digital Discovery|June 14, 2023
Designing catalysts with deep generative models and computational data. A case study for Suzuki cross coupling reactionsOliver Schilter, Alain Vaucher, Philippe Schwaller, et al.
Digital Discovery|August 18, 2025
Tango*: constrained synthesis planning using chemically informed value functionsDaniel Armstrong, Zlatko Jončev, Jeff Guo, et al.
Journal of the American Chemical Society|February 7, 2025
A Holistic Data-Driven Approach to Synthesis Predictions of Colloidal Nanocrystal ShapesLudovic Zaza, Bojana Ranković, Philippe Schwaller, et al.
Nature Communications|September 26, 2020
Transfer learning enables the molecular transformer to predict regio- and stereoselective reactions on carbohydratesGiorgio Pesciullesi, Philippe Schwaller, Teodoro Laino, et al.
Digital Discovery|November 28, 2023
Alchemical analysis of FDA approved drugsMarkus Orsi, Daniel Probst, Philippe Schwaller, et al.
Digital Discovery|April 17, 2023
Enhancing diversity in language based models for single-step retrosynthesisAlessandra Toniato, Alain C Vaucher, Philippe Schwaller, et al.
Chemical Science|August 10, 2018
"Found in Translation": predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence modelsPhilippe Schwaller, Théophile Gaudin, Dávid Lányi, et al.
Drug Discovery Today|February 7, 2020
Exploring chemical space using natural language processing methodologies for drug discoveryHakime Öztürk, Arzucan Özgür, Philippe Schwaller, et al.
Nature Communications|April 4, 2025
A multi-modal transformer for predicting global minimum adsorption energyJunwu Chen, Xu Huang, Cheng Hua, et al.
Pageof 6

Showing results (11-20 of 56) with videos related to

Sort By:
Pageof 6
Chimia|December 30, 2019
Data-driven Chemical Reaction Prediction and RetrosynthesisVishnu H Nair, Philippe Schwaller, Teodoro Laino
Digital Discovery|June 14, 2023
Designing catalysts with deep generative models and computational data. A case study for Suzuki cross coupling reactionsOliver Schilter, Alain Vaucher, Philippe Schwaller, et al.
Digital Discovery|August 18, 2025
Tango*: constrained synthesis planning using chemically informed value functionsDaniel Armstrong, Zlatko Jončev, Jeff Guo, et al.
Journal of the American Chemical Society|February 7, 2025
A Holistic Data-Driven Approach to Synthesis Predictions of Colloidal Nanocrystal ShapesLudovic Zaza, Bojana Ranković, Philippe Schwaller, et al.
Nature Communications|September 26, 2020
Transfer learning enables the molecular transformer to predict regio- and stereoselective reactions on carbohydratesGiorgio Pesciullesi, Philippe Schwaller, Teodoro Laino, et al.
Digital Discovery|November 28, 2023
Alchemical analysis of FDA approved drugsMarkus Orsi, Daniel Probst, Philippe Schwaller, et al.
Digital Discovery|April 17, 2023
Enhancing diversity in language based models for single-step retrosynthesisAlessandra Toniato, Alain C Vaucher, Philippe Schwaller, et al.
Chemical Science|August 10, 2018
"Found in Translation": predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence modelsPhilippe Schwaller, Théophile Gaudin, Dávid Lányi, et al.
Drug Discovery Today|February 7, 2020
Exploring chemical space using natural language processing methodologies for drug discoveryHakime Öztürk, Arzucan Özgür, Philippe Schwaller, et al.
Nature Communications|April 4, 2025
A multi-modal transformer for predicting global minimum adsorption energyJunwu Chen, Xu Huang, Cheng Hua, et al.
Pageof 6