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Found 3 papers, 2 papers with code
Revealing Model Biases: Assessing Deep Neural Networks via Recovered Sample Analysis
While a generalization test is one way to evaluate a trained model's performance, it can be costly and may not cover all scenarios to ensure that the model has learned the primary concepts.
BioLCNet: Reward-modulated Locally Connected Spiking Neural Networks
Brain-inspired computation and information processing alongside compatibility with neuromorphic hardware have made spiking neural networks (SNN) a promising method for solving learning tasks in machine learning (ML).
Towards Real-World BCI: CCSPNet, A Compact Subject-Independent Motor Imagery Framework
A conventional brain-computer interface (BCI) requires a complete data gathering, training, and calibration phase for each user before it can be used.
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