The purpose of Br. A. In. is to investigate key questions at the crossbreed of Artificial Intelligence, Graph Signal Processing and Neuroimagery. As of beginning of 2018, these questions include:
- Interpretability of Deep Learning,
- Incremental and Budget-Constrained Deep Learning,
- Graph Convolutional Neural Networks,
- Analysis of spatiotemporal patterns in multivariate domains,
- Binary Associative Memories.
Br. A. In. was created in the continuation of the NEUCOD project (led by Prof. Emeritus Claude Berrou) funded by the European Research Council (ERC FP7 290901), as well as the Neural Coding and Neural Communications project funded by the Britanny Region and the CominLabs LabEx.
Br. A. In. is currently jointly led by Pr. Vincent Gripon and Pr. Nicolas Farrugia.
Please check our open positions!