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Bottom-up Approaches to Machines dedicated to Bayesian Inference

Description du projet


Challenging current Thinking

We propose a theory and a hardware implementation of probabilistic computation inspired by biochemical cell signaling. We will study probabilistic computation following three axes: algebra, biology, and hardware. In each case, we will develop a bottom-up hierarchical approach starting from the elementary components, and study how to combine them to build more complex systems. We propose Bayesian gates operating on probability distributions on binary variables as the building blocks of our probabilistic algebra. These Bayesian gates can be seen as a generalization of logical operators in Boolean algebra. We propose to interpret elementary cell signaling pathways as biological implementation of these probabilistic gates. In turn, the key features of biochemical processes give new insights for innovative probabilistic hardware implementation. We propose to associate conventional electronics and novel stochastic nano-devices to build the required hardware elements. Combining them will lead to new artificial information processing systems, which could, in the future, outperform classical computers in tasks involving a direct interaction with the physical world. For these purposes, the BAMBI project associates research in Bayesian probability theory, molecular biology, nanophysics, computer science and electronics.

Appel à propositions

FP7-ICT-2013-C
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Coordinateur

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Contribution de l’UE
€ 1 085 316,00
Adresse
RUE MICHEL ANGE 3
75794 Paris
France

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Région
Ile-de-France Ile-de-France Paris
Type d’activité
Research Organisations
Contact administratif
Julie Zittel (Mrs.)
Liens
Coût total
Aucune donnée

Participants (5)