Niklas Andreas Pfister

Niklas Andreas Pfister

Assistant professor, tenure track, Associate Professor

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    1. 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

    2. Published

      Supervised learning and model analysis with compositional data

      hrt620, hrt620, Ailer, E., Kilbertus, N. & Pfister, Niklas Andreas, 2023, In: PLOS Computational Biology. 19, 6, e1011240.

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

    3. 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

    4. 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

    5. 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

    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. 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

    8. 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

    9. 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

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

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