About
I am an indefinite-term (tenured) Senior Research Scientist at RIKEN AIP, affiliated with the Adaptive Bayesian Intelligence Team and a core member of the Bayes-Duality project. Before, I was a postdoctoral researcher with Emtiyaz Khan. I completed my PhD in the Computer Vision Group at TU Munich with Daniel Cremers.
My research aims to advance both the theory and practice of deep learning. I am currently interested in optimization and variational Bayesian principles to achieve this goal.
News
- 2026-07-06 I will be at ICML 2026 (July 6-11) in Seoul!
- 2026-06-28 Attending ISBA 2026 from June 28 to July 3 in Nagoya, Japan for an invited talk.
- 2026-06-15 Attending the 4th Bayes-Duality Workshop from June 15-26.
- 2026-05-30 Visiting Munich until June 12; giving a tutorial at the Helmholtz AI Conference (HAICON26).
- 2026-05-10 One paper accepted at TMLR!
- 2026-05-05 Four papers (two posters, one spotlight, one position paper) accepted at ICML 2026. See you in Seoul!
- 2026-04-23 Attending ICLR 2026 in Rio de Janeiro and presenting a poster on Bayesian-ADMM.
- 2026-04-01 I am thankful to receive a KAKENHI grant (JPY41,600,000) for my research on variational Bayesian deep learning. For open positions and more details, see the page on the Variational AI project.
- 2026-03-25 Invited talk at the 2nd RIKEN AIP-IIT Hyderabad Workshop (virtual).
- 2026-03-01 Serving as an area chair for ProbML 2026.
- 2026-01-30 One paper accepted at ICLR 2026 (Rio de Janeiro), and one paper accepted at CPAL 2026 (Tübingen).
- 2025-12-12 I'm an area chair for ICML 2026.
- 2025-12-02 Attending NeurIPS in San Diego (presenting two posters).
Selected Publications
- T. Möllenhoff*, S. Swaroop*, F. Doshi-Velez, M. E. Khan. Federated ADMM from Bayesian Duality, In Proceedings of the International Conference on Learning Representations (ICLR), 2026. [code]
- Y. Shen*, N. Daheim*, B. Cong, P. Nickl, G. M. Marconi, C. Bazan, R. Yokota, I. Gurevych, D. Cremers, M. E. Khan, T. Möllenhoff. Variational Learning is Effective for Large Deep Networks. In Proceedings of the International Conference on Machine Learning (ICML), 2024. [code]
- T. Möllenhoff, M. E. Khan. SAM as an Optimal Relaxation of Bayes. In Proceedings of the International Conference on Learning Representations (ICLR), 2023. [code]
- T. Frerix*, T. Möllenhoff*, M. Moeller*, D. Cremers. Proximal Backpropagation. In Proceedings of the International Conference on Learning Representations (ICLR), 2018. [code]