Tassilo Schwarz

Status

Postgraduate Student

Mathematics of Random Systems Doctoral Training Programme

Contact form

https://tassilo-schwarz.com/

ORCID iD

https://orcid.org/0009-0002-3512-6191

Research groups

Machine Learning and Data Science

Address

Mathematical Institute
University of Oxford
Andrew Wiles Building
Radcliffe Observatory Quarter
Woodstock Road
Oxford
OX2 6GG

Major / recent publications

Up-to-date information on my website tassilo-schwarz.com.

Preprints

T. Schwarz, C. Dieball, C. Kogler, K. Lam, R. Lambiotte, A. Doucet, A. Godec, and G. Deligiannidis, Permutation-Invariant Spectral Learning via Dyson Diffusion, arXiv:2510.08535.

T. Schwarz, A. B. Kolomeisky, and A. Godec, Mind the Memory: Consistent Time Reversal Removes Artefactual Scaling of Energy Dissipation Rate and Provides More Accurate and Reliable Thermodynamic Inference, arXiv:2410.11819.

Accepted

C. L. Amado, T. Schwarz, Y. Tian, and R. Lambiotte, Complex-Weighted Convolutional Networks: Provable Expressiveness via Complex Diffusion, in Proceedings of the Fourth Learning on Graphs Conference (PMLR, 2026, accepted. preprint link)

L. A. Goldberg, M. Roth, and T. Schwarz, Parameterised approximation of the fixation probability of the dominant mutation in the multi-type Moran process, Theoretical Computer Science 1016, 114785 (2024).

Prizes, awards, and scholarships

Rhodes Scholarship

Recent publications

Permutation-Invariant Spectral Learning via Dyson Diffusion

Schwarz, T Dieball, C Kogler, C Lam, K Lambiotte, R Doucet, A Godec, A Deligiannidis, G (09 Oct 2025)

Parameterised approximation of the fixation probability of the dominant mutation in the multi-type Moran process

Goldberg, L Roth, M Schwarz, T Theoretical Computer Science volume 1016 (22 Aug 2024)

<p>Open Consultation on Copyright and Artificial Intelligence</p>

Gangjee, D Atilla, S Crais, L Fan, J Gurumurthy, J Harvey, C Hall, S Karim, M Lubke, G da Cunha Mota, J Müller, E Nanji, F Mathew, S Railton, A Schwarz, T Wong, M Wong, C Yasmine, Z Zhao, Y Cho, D

Teaching

HT 2026: C8.2 Stochastic Analysis and PDEs
MT 2025: B8.1 Probability, Measure and Martingales
HT 2025: C8.2 Stochastic Analysis and PDEs
MT 2024: B8.1 Probability, Measure and Martingales
MT 2023: B4.3 Distribution Theory