Research output per year
Research output per year
Personal profile
Short presentation
I'm a PhD student in Statistics at the Copenhagen Causality Lab with Prof. Jonas Peters. I work in the fields of causal inference and machine learning. To learn more, please visit my webpage.
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Family‐based preventive intervention for children of parents with severe mental illness: A randomized clinical trial
Müller, A. D., Gjøde, I. C. T., Thams, N., Ingversen, S., Moszkowicz, M., Jepsen, J. R. M., Mikkelsen, L. J., Nielsen, S. S., Hemager, N., Nordentoft, M. & Thorup, A. A. E., 2024, In: JCPP Advances. 4, 3, 16 p., e12216.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile1 Downloads (Pure) -
Local Independence Testing for Point Processes
Thams, N. & Hansen, N. R., 2024, In: IEEE Transactions on Neural Networks and Learning Systems. 35, 4, p. 4902-4910Research output: Contribution to journal › Journal article › Research › peer-review
File1 Citation (Scopus)14 Downloads (Pure) -
Invariant Policy Learning: A Causal Perspective
Saengkyongam, S., Thams, N., Peters, J. & Pfister, N., 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
Open AccessFile3 Citations (Scopus)14 Downloads (Pure) -
Statistical testing under distributional shifts
Thams, N., Saengkyongam, S., Pfister, N. & Peters, J., 2023, In: Journal of the Royal Statistical Society, Series B (Statistical Methodology). 85, 3, p. 597-663Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile1 Citation (Scopus)22 Downloads (Pure) -
Causality and Distribution Shift
Thams, N. T. B., 2022, 379 p.Research output: Book/Report › Ph.D. thesis › Research
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Evaluating Robustness to Dataset Shift via Parametric Robustness Sets
Thams, N., 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 proceeding › Article in proceedings › Research › peer-review
Open AccessFile2 Citations (Scopus)5 Downloads (Pure) -
Regularizing towards Causal Invariance: Linear Models with Proxies
Oberst, M., Thams, N. T. B., 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 proceeding › Article in proceedings › Research › peer-review
Open AccessFile15 Downloads (Pure) -
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values
Weichwald, S., Emil Jakobsen, M., Mogensen, P. B., Petersen, L., Thams, N. T. & 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 proceeding › Article in proceedings › Research › peer-review
Open AccessFile44 Downloads (Pure)