Thrifty AI
How to find efficient representations in the low data regime (typically few-shot or few-label learning).
A research team in Brest, France
We study representations that help intelligent systems learn, adapt, and make sense of complex data.
01 / RESEARCH
BRAIN is a research team of Lab-STICC (CNRS UMR 6285) hosted at IMT Atlantique and part of the Mathematical and Electrical Engineering (MEE) department.
The purpose of BRAIN is to investigate key questions at the crossbreed of Artificial Intelligence, Deep Learning and Signal Processing, with applications using images, sounds, text and more complex domains including neuroimaging data.
How to find efficient representations in the low data regime (typically few-shot or few-label learning).
How to find efficient representations to lower the demand in computations and energy of AI systems, typically for AI on edge.
How to leverage the geometry of latent spaces or input domains to better adapt and monitor AI systems.
02 / SELECTED WORK
A selection of research from the team. Explore more of our publications in HAL.
All publicationsA foundation model designed to adapt to diverse EEG recording setups.
A kernel perspective on adapting vision-language models from few examples.
03 / PEOPLE
Researchers, engineers, and doctoral students working across disciplines.
All team membersPERMANENT RESEARCHERS
Our team also includes research engineers, postdoctoral researchers, and PhD students. Meet everyone ↗
04 / CONNECT
Discover our research, code, and collaborations.