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AkshatKumar Nigam

Showing results (1-10 of 17) with videos related to

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Digital Discovery|September 12, 2022
Parallel tempered genetic algorithm guided by deep neural networks for inverse molecular designAkshatKumar Nigam, Robert Pollice, Alán Aspuru-Guzik
Chemical Reviews|June 9, 2025
Studying Noncovalent Interactions in Molecular Systems with Machine LearningSerhii Tretiakov, AkshatKumar Nigam, Robert Pollice
Chemical Science|February 16, 2024
Artificial design of organic emitters <i>via</i> a genetic algorithm enhanced by a deep neural networkAkshatKumar Nigam, Robert Pollice, Pascal Friederich, et al.
Chemical Science|June 14, 2021
Beyond generative models: superfast traversal, optimization, novelty, exploration and discovery (STONED) algorithm for molecules using SELFIESAkshatKumar Nigam, Robert Pollice, Mario Krenn, et al.
Digital Discovery|November 28, 2023
Recent advances in the self-referencing embedded strings (SELFIES) libraryAlston Lo, Robert Pollice, AkshatKumar Nigam, et al.
Biorxiv : the Preprint Server for Biology|June 9, 2023
SLC12A9 is a lysosome-detoxifying ammonium - chloride co-transporterRoni Levin-Konigsberg, Koushambi Mitra, AkshatKumar Nigam, et al.
Expert Opinion on Drug Discovery|June 15, 2021
Assigning confidence to molecular property predictionAkshatKumar Nigam, Robert Pollice, Matthew F D Hurley, et al.
Accounts of Chemical Research|February 2, 2021
Data-Driven Strategies for Accelerated Materials DesignRobert Pollice, Gabriel Dos Passos Gomes, Matteo Aldeghi, et al.
Biorxiv : the Preprint Server for Biology|October 10, 2024
Prediction and design of transcriptional repressor domains with large-scale mutational scans and deep learningRaeline Valbuena, AkshatKumar Nigam, Josh Tycko, et al.
Journal of the American Chemical Society|January 12, 2022
A Comprehensive Discovery Platform for Organophosphorus Ligands for CatalysisTobias Gensch, Gabriel Dos Passos Gomes, Pascal Friederich, et al.
Pageof 2

Showing results (1-10 of 17) with videos related to

Sort By:
Pageof 2
Digital Discovery|September 12, 2022
Parallel tempered genetic algorithm guided by deep neural networks for inverse molecular designAkshatKumar Nigam, Robert Pollice, Alán Aspuru-Guzik
Chemical Reviews|June 9, 2025
Studying Noncovalent Interactions in Molecular Systems with Machine LearningSerhii Tretiakov, AkshatKumar Nigam, Robert Pollice
Chemical Science|February 16, 2024
Artificial design of organic emitters <i>via</i> a genetic algorithm enhanced by a deep neural networkAkshatKumar Nigam, Robert Pollice, Pascal Friederich, et al.
Chemical Science|June 14, 2021
Beyond generative models: superfast traversal, optimization, novelty, exploration and discovery (STONED) algorithm for molecules using SELFIESAkshatKumar Nigam, Robert Pollice, Mario Krenn, et al.
Digital Discovery|November 28, 2023
Recent advances in the self-referencing embedded strings (SELFIES) libraryAlston Lo, Robert Pollice, AkshatKumar Nigam, et al.
Biorxiv : the Preprint Server for Biology|June 9, 2023
SLC12A9 is a lysosome-detoxifying ammonium - chloride co-transporterRoni Levin-Konigsberg, Koushambi Mitra, AkshatKumar Nigam, et al.
Expert Opinion on Drug Discovery|June 15, 2021
Assigning confidence to molecular property predictionAkshatKumar Nigam, Robert Pollice, Matthew F D Hurley, et al.
Accounts of Chemical Research|February 2, 2021
Data-Driven Strategies for Accelerated Materials DesignRobert Pollice, Gabriel Dos Passos Gomes, Matteo Aldeghi, et al.
Biorxiv : the Preprint Server for Biology|October 10, 2024
Prediction and design of transcriptional repressor domains with large-scale mutational scans and deep learningRaeline Valbuena, AkshatKumar Nigam, Josh Tycko, et al.
Journal of the American Chemical Society|January 12, 2022
A Comprehensive Discovery Platform for Organophosphorus Ligands for CatalysisTobias Gensch, Gabriel Dos Passos Gomes, Pascal Friederich, et al.
Pageof 2