Nikolaj Theodor Birkmose Thams

Nikolaj Theodor Birkmose Thams

Enrolled PhD student


Publication year:
  1. 2024
  2. E-pub ahead of print

    Local Independence Testing for Point Processes

    Thams, Nikolaj Theodor Birkmose & Hansen, Niels Richard, 2024, (E-pub ahead of print) In: IEEE Transactions on Neural Networks and Learning Systems. p. 1-12 12 p.

    Research output: Contribution to journalJournal articlepeer-review

  3. 2023
  4. 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

  5. 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

  6. 2022
  7. Published

    Evaluating Robustness to Dataset Shift via Parametric Robustness Sets

    Thams, Nikolaj Theodor Birkmose, Oberst, M. & Sontag, D., 2022, Advances in Neural Information Processing Systems 35 - 36th Conference on Neural Information Processing Systems, NeurIPS 2022. Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A. (eds.). NeurIPS Proceedings, p. 1-45 (Advances in Neural Information Processing Systems, Vol. 35).

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

  8. Published

    Causality and Distribution Shift

    Thams, Nikolaj Theodor Birkmose, 2022, 379 p.

    Research output: Book/ReportPh.D. thesis

  9. 2021
  10. Published

    Regularizing towards Causal Invariance: Linear Models with Proxies

    Oberst, M., Thams, Nikolaj Theodor Birkmose, Peters, J. M. & Sontag, D., 2021, Proceedings of the 38th International Conference on Machine Learning (ICML). PMLR, p. 1-11 (Proceedings of Machine Learning Research, Vol. 139).

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

  11. 2020
  12. Published

    Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values

    Weichwald, Sebastian, Emil Jakobsen, M., Mogensen, Phillip Bredahl, Petersen, L., Thams, Nikolaj Theodor Birkmose & Varando, G., 2020, Proceedings of the NeurIPS 2019 Competition and Demonstration Track. PMLR, p. 27-36 (Proceedings of Machine Learning Research, Vol. 123).

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

ID: 165238204