Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks
Safety-critical sensory applications, like medical diagnosis, demand accurate decisions from
limited, noisy data. Bayesian neural networks excel at such tasks, offering predictive …
limited, noisy data. Bayesian neural networks excel at such tasks, offering predictive …
CiM-BNN: Computing-in-MRAM Architecture for Stochastic Computing Based Bayesian Neural Network
Bayesian neural network (BNN) has gradually attracted researchers' attention with its
uncertainty representation and high robustness. However, high computational complexity …
uncertainty representation and high robustness. However, high computational complexity …
ReAIM: A ReRAM-based Adaptive Ising Machine for Solving Combinatorial Optimization Problems
Recently, in light of the success of quantum computers, research teams have actively
developed quantum-inspired computers using classical computing technology. One notable …
developed quantum-inspired computers using classical computing technology. One notable …
An energy-efficient Bayesian neural network accelerator with CiM and a time-interleaved Hadamard digital GRNG using 22-nm finFET
Bayesian neural networks (BNNs) have been proposed to address the problems of
overfitting and overconfident decision making, common in conventional neural networks …
overfitting and overconfident decision making, common in conventional neural networks …