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Domain Generalization through Meta-Learning: A Survey
Deep neural networks (DNNs) have revolutionized artificial intelligence but often lack performance when faced with out-of-distribution (OOD) data, a common scenario due to the inevitable domain shifts in real-world applications.
Meta-Learning in Spiking Neural Networks with Reward-Modulated STDP
The human brain constantly learns and rapidly adapts to new situations by integrating acquired knowledge and experiences into memory.
A least squares support vector regression for anisotropic diffusion filtering
Anisotropic diffusion filtering for signal smoothing as a low-pass filter has the advantage of the edge-preserving, i. e., it does not affect the edges that contain more critical data than the other parts of the signal.
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