Niklas Andreas Pfister

Niklas Andreas Pfister

Assistant professor, tenure track, Associate Professor

Member of:


    Publication year:
    1. 2023
    2. Published

      Invariant Policy Learning: A Causal Perspective

      Saengkyongam, S., Thams, Nikolaj Theodor Birkmose, Peters, J. & Pfister, Niklas Andreas, 2023, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 45, 7, p. 8606-8620 15 p.

      Research output: Contribution to journalJournal articlepeer-review

    3. Published

      Statistical testing under distributional shifts

      Thams, Nikolaj Theodor Birkmose, Saengkyongam, S., Pfister, Niklas Andreas & Peters, J., 2023, In: Journal of the Royal Statistical Society, Series B (Statistical Methodology). 85, 3, p. 597-663

      Research output: Contribution to journalJournal articlepeer-review

    4. Published

      Supervised learning and model analysis with compositional data

      Huang, Shimeng, Ailer, E., Kilbertus, N. & Pfister, Niklas Andreas, 2023, In: PLOS Computational Biology. 19, 6, e1011240.

      Research output: Contribution to journalJournal articlepeer-review

    5. 2022
    6. Published

      A Causal Framework for Distribution Generalization

      Christiansen, R., Pfister, Niklas Andreas, Emil Jakobsen, M., Gnecco, N. & Peters, J. M., 2022, In: I E E E Transactions on Pattern Analysis and Machine Intelligence. 44, 10, p. 6614-6630 17 p.

      Research output: Contribution to journalJournal articlepeer-review

    7. Published

      Identifiability of Sparse Causal Effects using Instrumental Variables

      Pfister, Niklas Andreas & Peters, J., 2022, Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence. PMLR, p. 1613-1622 10 p. (Proceedings of Machine Learning Research, Vol. 180).

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    8. Published

      Interpreting tree ensemble machine learning models with endoR

      Ruaud, A., Pfister, Niklas Andreas, Ley, R. E. & Youngblut, N. D., 2022, In: PLOS Computational Biology. 18, 12, 39 p., e1010714.

      Research output: Contribution to journalJournal articlepeer-review

    9. Published

      Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning

      Weichwald, Sebastian, Wengel Mogensen, S., Lee, T. E., Baumann, D., Kroemer, O., Guyon, I., Trimpe, S., Peters, J. M. & Pfister, Niklas Andreas, 2022, Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track. PMLR, p. 246-258 (Proceedings of Machine Learning Research, Vol. 176).

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    10. Published

      Multiomic profiling of the liver across diets and age in a diverse mouse population

      Williams, E. G., Pfister, Niklas Andreas, Roy, S., Statzer, C., Haverty, J., Ingels, J., Bohl, C., Hasan, M., Čuklina, J., Bühlmann, P., Zamboni, N., Lu, L., Ewald, C. Y., Williams, R. W. & Aebersold, R., 2022, In: Cell Systems. 13, 1, p. 43-57, e1-6

      Research output: Contribution to journalJournal articlepeer-review

    11. 2021
    12. Published

      Stabilizing variable selection and regression

      Pfister, Niklas Andreas, Williams, E. G., Peters, J., Aebersold, R. & Bühlmann, P., 2021, In: Annals of Applied Statistics. 15, 3, p. 1220-1246

      Research output: Contribution to journalJournal articlepeer-review

    13. 2019
    14. Published

      Invariant Causal Prediction for Sequential Data

      Pfister, Niklas Andreas, Bühlmann, P. & Peters, J., 2019, In: Journal of the American Statistical Association. 114, 527, p. 1264-1276 13 p.

      Research output: Contribution to journalJournal articlepeer-review

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