Projects funded by the NCN


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6 projects found matching your search criteria :

  1. Local Causal Explainability of Machine Learning Models: Game-Theoretic Methods for Reliable Feature Attribution

    Call: PRELUDIUM 24 , Panel: ST6

    Principal investigator: Mateusz Maciej Gajewski

    Politechnika Poznańska

  2. NMR Spectroscopy as Molecular Language: A Deep Learning Approach to Bioactivity Prediction

    Call: PRELUDIUM 24 , Panel: NZ7

    Principal investigator: Arkadiusz Bogumił Leniak

    Instytut Farmakologii PAN

  3. XAICancer: Explainable Artificial Intelligence for Cancer Imaging

    Call: SONATA BIS 13 , Panel: ST6

    Principal investigator: dr Neo Christopher Chung

    Uniwersytet Warszawski, Wydział Matematyki, Informatyki i Mechaniki

  4. Improving interpretability properties of prototypical parts-based deep neural networks.

    Call: PRELUDIUM 21 , Panel: ST6

    Principal investigator: Dawid Damian Rymarczyk

    Uniwersytet Jagielloński, Wydział Matematyki i Informatyki

  5. Interpretability of Deep Neural Networks for Radiomics

    Call: CHIST-ERA2019 , Panel: ST6

    Principal investigator: dr Neo Christopher Honghoon Chung

    Uniwersytet Warszawski, Wydział Matematyki, Informatyki i Mechaniki

  6. Can an artificial neural network teach us quantum physics?

    Call: PRELUDIUM 17 , Panel: ST2

    Principal investigator: Anna Maria Dawid-Łękowska

    Uniwersytet Warszawski, Wydział Fizyki