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Gradient Scaling on Deep Spiking Neural Networks with Spike-Dependent Local Information
Deep spiking neural networks (SNNs) are promising neural networks for their model capacity from deep neural network architecture and energy efficiency from SNNs' operations.
Field-tunable toroidal moment in a chiral-lattice magnet
A toroidal dipole moment appears independent of the electric and magnetic dipole moment in the multipole expansion of electrodynamics.
Strongly Correlated Electrons Materials Science
Deep neural network Grad-Shafranov solver constrained with measured magnetic signals
A neural network solving Grad-Shafranov equation constrained with measured magnetic signals to reconstruct magnetic equilibria in real time is developed.
Markov chain Hebbian learning algorithm with ternary synaptic units
In spite of remarkable progress in machine learning techniques, the state-of-the-art machine learning algorithms often keep machines from real-time learning (online learning) due in part to computational complexity in parameter optimization.
