Nikolaj Thams

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 11

Top Topics

Causal Structure

Point Processes

Top Venues

IEEE Trans. Neural Networks Learn. Syst.

IEEE Trans. Pattern Anal. Mach. Intell.

Publications

Nikolaj Thams, Niels Richard Hansen
Local Independence Testing for Point Processes. IEEE Trans. Neural Networks Learn. Syst. 35 (4) (2024)
Sorawit Saengkyongam, Nikolaj Thams, Jonas Peters, Niklas Pfister
Invariant Policy Learning: A Causal Perspective. IEEE Trans. Pattern Anal. Mach. Intell. 45 (7) (2023)
Phillip B. Mogensen, Nikolaj Thams, Jonas Peters
Invariant Ancestry Search. CoRR (2022)
Nikolaj Thams, Michael Oberst, David A. Sontag
Evaluating Robustness to Dataset Shift via Parametric Robustness Sets. CoRR (2022)
Nikolaj Thams, Michael Oberst, David A. Sontag
Evaluating Robustness to Dataset Shift via Parametric Robustness Sets. NeurIPS (2022)
Phillip B. Mogensen, Nikolaj Thams, Jonas Peters
Invariant Ancestry Search. ICML (2022)
Sorawit Saengkyongam, Nikolaj Thams, Jonas Peters, Niklas Pfister
Invariant Policy Learning: A Causal Perspective. CoRR (2021)
Michael Oberst, Nikolaj Thams, Jonas Peters, David A. Sontag
Regularizing towards Causal Invariance: Linear Models with Proxies. ICML (2021)
Michael Oberst, Nikolaj Thams, Jonas Peters, David A. Sontag
Regularizing towards Causal Invariance: Linear Models with Proxies. CoRR (2021)
Sebastian Weichwald, Martin E. Jakobsen, Phillip B. Mogensen, Lasse Petersen, Nikolaj Thams, Gherardo Varando
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values. CoRR (2020)
Sebastian Weichwald, Martin E. Jakobsen, Phillip B. Mogensen, Lasse Petersen, Nikolaj Thams, Gherardo Varando
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values. NeurIPS (Competition and Demos) (2019)