Presently I’m a postdoc in the group of Kaie Kubjas at Aalto University, Finland. Before that, I spent a year in the non-linear algebra group of Bernd Sturmfels at the Max-Planck-Institute for Mathematics in the Sciences, Leipzig.

I received my PhD within the MathCoRe research training group at Otto-von-Guericke-Universität Magdeburg under the supervision of Thomas Kahle and Volker Kaibel working on a topic in algebraic statistics.

I have a broad interest in the fundamental laws and limits in probability, information theory and geometry. My research is focussed on *conditional independence*: suppose you observe some factors in a (random) experiment; how does that knowledge change the interdependence of the unobserved factors? This is a question in the area of *probabilistic reasoning* and I am looking for the universal laws governing such reasoning tasks — and ways to prove them algebraically using computers.

The analogue to have in mind is Pappus’s theorem in plane geometry. But instead of points and collinearity, I want to discover the hidden relations of random variables in terms of stochastic independence.

These topics touch algebra, statistics, geometry and computer science. I maintain the website gaussoids.de which contains various computer-readable data about Gaussian conditional independence structures and related objects.

- Here is my full CV (last updated 06 July 2022).

T. Boege:

**Selfadhesivity in Gaussian conditional independence structures**, Proceedings of the 12th Workshop on Uncertainty Processing (WUPES ’22), May 2022,`cs.IT/2205.07667`

, MathRepo:`SelfadhesiveGaussianCI`

.T. Boege:

**No eleventh conditional Ingleton inequality**, Apr 2022,`cs.IT/2204.03971`

, MathRepo:`ConditionalIngleton`

.T. Boege, S. Petrović, and B. Sturmfels:

**Marginal Independence Models**, Proceedings of the 47th International Symposium on Symbolic and Algebraic Computation 2022:263–271, 2022, DOI:10.1145/3476446.3536193,`math.ST/2112.10287`

. MathRepo:`MarginalIndependence`

, auxiliary code and data:`CI-models-from-graphs`

.T. Boege, T. Kahle, A. Kretschmer, F. Röttger:

**The geometry of Gaussian double Markovian distributions**, Scandinavian Journal of Statistics, 2022, DOI:10.1111/sjos.12604,`math.ST/2107.00134`

. Data: Double Markovian relations.T. Boege:

**Incidence geometry in the projective plane via almost-principal minors of symmetric matrices**, Mar 2021,`math.ST/2103.02589`

.T. Boege:

**Gaussoids are two-antecedental approximations of Gaussian conditional independence structures**, Annals of Mathematics and Artificial Intelligence 90:645–673, 2022, DOI:10.1007/s10472-021-09780-0,`math.ST/2010.11914`

. Code related to computations:`gaussant-code`

. The published version contained misprints for a couple of months. They have been corrected under the above DOI and a statement was published here.T. Boege, J. I. Coons, C. Eur, A. Maraj, and F. Röttger:

**Reciprocal Maximum Likelihood Degrees of Brownian Motion Tree Models**, Le Matematiche 76(2):383–398, 2021, DOI:10.4418/2021.76.2.6,`math.ST/2009.11849`

.T. Boege, and T. Kahle:

**Construction Methods for Gaussoids**, Kybernetika 56(6):1045–1062, 2020, DOI:10.14736/kyb-2020-6-1045,`math.CO/1902.11260`

. Data: Special gaussoids.T. Boege, A. D’Alì, T. Kahle, and B. Sturmfels:

**The Geometry of Gaussoids**, Foundations of Computational Mathematics, 19(4):775–812, 2019, DOI:10.1007/s10208-018-9396-x,`math.CO/1710.07175`

. Data: Gaussoids.de.

T. Boege:

**The Gaussian conditional independence inference problem**,*doctoral dissertation, Otto-von-Guericke-Universität Magdeburg*, June 2022, DOI:10.25673/86275. dissert.pdf (published version), Defense slides.T. Boege:

**Construction Methods for Gaussoids**,*M.Sc. thesis, Otto-von-Guericke-Universität Magdeburg*, Sep 2018, mthesis.pdf.T. Boege:

**On Permutations with Decidable Cycles**,*B.Sc. thesis, Otto-von-Guericke-Universität Magdeburg*, Dec 2016,`math.LO/1612.05136`

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