Humans, animals, and other living beings have a natural ability to autonomously learn throughout their lives and quickly adapt to their surroundings, but computers lack such abilities. Our goal is to bridge such gaps between the learning of living-beings and computers. We are machine learning researchers with an expertise in areas such as approximate inference, Bayesian statistics, continuous optimization, information geometry, etc. We work on a variety of learning problems, especially those involving supervised, continual, active, federated, online, and reinforcement learning. Please check out research and publications pages for a more exhaustive overview.
If you are interested in joining us, see the people page and the vacancies below for current opportunities.
Vacancies
RIKEN Special Post-Doc Researcher:Special Postdoctoral Researcher (SPDR) for FY 2027; closing date is April 2nd, 2026. [details]
Internship (Overseas Student Collaboration) Program:Masters or PhD students from overseas, collaborative research for 3-12 months with financial support. [details]
Junior Research Associate:Part-time positions at RIKEN for young researchers enrolled in Japanese university PhD programs. [details]
International Program Associate:RIKEN’s joint graduate school program for non-Japanese PhD candidates at any graduate school. [details]
PhD and PostDoc at TU Darmstadt (Germany):Positions available for a new ABI group at TU Darmstadt (Germany), starting Sep. 2026.
For all positions, send inquiries to jobs-abi [at] googlegroups.com.News
Federated ADMM from Bayesian Duality by Thomas Möllenhoff et al. accepted at ICLR 2026
New pre-prints
- Log-Normal Multiplicative Dynamics for Stable Low-Precision Training of Large Networks.
- SVRG and Beyond via Posterior Correction.
Emtiyaz Khan: Keynote at the 1st EurIPS conference (officially endorsed European version of NeurIPS) [slides].
Thomas, Hugo, and Christopher will present their works at the RIKEN AIP LLMxML Workshop.