Stochastic machines dedicated to Bayesian inference
Source localization and separation PhD thesis of Raphael frisch (2019) Computers are without doubt one of the most important invention
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Hardware
Skyrmion Gas Manipulation for Probabilistic Computing
The topologically protected magnetic spin configurations known as Skyrmions offer promising applications due to their stability, mobility, and localization. We
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Design of Stochastic Machines Dedicated to Approximate Bayesian inferences
PhD thesis of Marvin Faix (2016) The aim of this research is to design computers best suited to do probabilistic
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Cell signaling as a probabilistic computer
Cell signaling as a probabilistic computer PostDoc de David Colliaux (2016) Living organisms survive and multiply even though they have
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Bayesian Inference With Muller C-Elements
Bayesian inference is a powerful approach for integrating independent conflicting information for decision-making. Though an important component of robotic, biological,
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