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Stochastic Domain Wall-Magnetic Tunnel Junction Artificial Neurons for Noise-Resilient Spiking Neural Networks
The spatiotemporal nature of neuronal behavior in spiking neural networks (SNNs) make SNNs promising for edge applications that require high energy efficiency.
Shape-Dependent Multi-Weight Magnetic Artificial Synapses for Neuromorphic Computing
In neuromorphic computing, artificial synapses provide a multi-weight conductance state that is set based on inputs from neurons, analogous to the brain.
Controllable reset behavior in domain wall-magnetic tunnel junction artificial neurons for task-adaptable computation
Neuromorphic computing with spintronic devices has been of interest due to the limitations of CMOS-driven von Neumann computing.
Mesoscale and Nanoscale Physics
PAC Learning Guarantees Under Covariate Shift
We consider the Domain Adaptation problem, also known as the covariate shift problem, where the distributions that generate the training and test data differ while retaining the same labeling function.
