Selected Papers

More papers

  • Human interpretable structure-property relationships in chemistry using explainable machine learning and large language models

    Nat. Commun. Chem., 2025

    Paper · Code

  • Neural potentials of proteins extrapolate beyond training data

    J. Chem. Phys., 2023

    Paper

  • A perspective on explanations of molecular prediction models

    J. Chem. Theory Comput., 2023

    Paper

  • Do large language models know chemistry?

    Digital Discovery, 2023

    Paper · Code

  • Model agnostic generation of counterfactual explanations for molecules

    Chem. Sci., 2022

    Paper · Code

  • Graph neural network based coarse-grained mapping prediction

    Chem. Sci., 2020

    Paper · Code

Selected Talks

More talks

  • Extrapolating with CG neural potentials

    Summer of Chemical Theory @ WashU — Invited talk

    May 2023

  • Can CG neural potentials extrapolate beyond training data?

    ACS Spring 2023 — Invited talk

    March 2023

  • Model Agnostic Counterfactual Explanations for Molecular Property Predictions

    EPFL ISIC ML Seminar — Invited talk

    November 2022

  • Model Agnostic Molecular Counterfactual Explanations for Molecules

    ICLR 2022 — Invited talk

    April 2022