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Found 3 papers, 1 papers with code
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
FaiR-N: Fair and Robust Neural Networks for Structured Data
Fairness in machine learning is crucial when individuals are subject to automated decisions made by models in high-stake domains.
Explaining Deep Classification of Time-Series Data with Learned Prototypes
We improve upon existing models by optimizing for increased prototype diversity and robustness, visualize how these prototypes in the latent space are used by the model to distinguish classes, and show that prototypes are capable of learning features on two dimensional time-series data to produce explainable insights during classification tasks.
