Niklas Andreas Pfister

Niklas Andreas Pfister

Assistant professor, tenure track, Associate Professor

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    Publication year:
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    1 - 10 out of 13Page size: 10
    1. 2018
    2. Published

      Kernel-based tests for joint independence

      Pfister, Niklas Andreas, Bühlmann, P., Schölkopf, B. & Peters, J., 1 Jan 2018, In: Journal of the Royal Statistical Society, Series B (Statistical Methodology). 80, 1, p. 5-31 27 p.

      Research output: Contribution to journal › Journal article › Research › peer-review

    3. 2019
    4. 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 journal › Journal article › Research › peer-review

    5. Published

      Learning stable and predictive structures in kinetic systems

      Pfister, Niklas Andreas, Bauer, S. & Peters, J., 2019, In: Proceedings of the National Academy of Sciences of the United States of America. 116, 51, p. 25405-25411

      Research output: Contribution to journal › Journal article › Research › peer-review

    6. Published

      Robustifying independent component analysis by adjusting for group-wise stationary noise

      Pfister, Niklas Andreas, Weichwald, Sebastian, Bühlmann, P. & Schölkopf, B., 2019, In: Journal of Machine Learning Research. 20, 50 p., 147.

      Research output: Contribution to journal › Journal article › Research › peer-review

    7. 2021
    8. 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 journal › Journal article › Research › peer-review

    9. 2022
    10. 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 journal › Journal article › Research › peer-review

    11. 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 proceeding › Article in proceedings › Research › peer-review

    12. 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 journal › Journal article › Research › peer-review

    13. 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 proceeding › Article in proceedings › Research › peer-review

    14. 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 journal › Journal article › Research › peer-review

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