Developing Transparent Neural Architectures for Human Cognition
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This research focuses on developing transparent deep learning architectures that can model human cognitive processes while remaining interpretable to researchers. By combining the power of modern neural networks with the explainability needed in cognitive science, this work aims to advance our understanding of both human and machine learning.