Memristors, or resistive memory devices (RRAM) are nanometer-sized electronic components that can serve as memories for portable computers and other devices. When they are organized in a cross-bar structure, these tiny memories can be used to perform matrix multiplications with low energetic requirements.
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A machine learning framework that exploits memristor variability to implement Markov chain Monte Carlo sampling
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