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Found 2 papers, 1 papers with code
Working memory facilitates reward-modulated Hebbian learning in recurrent neural networks
Reservoir computing is a powerful tool to explain how the brain learns temporal sequences, such as movements, but existing learning schemes are either biologically implausible or too inefficient to explain animal performance.
Algorithmic Composition of Melodies with Deep Recurrent Neural Networks
A big challenge in algorithmic composition is to devise a model that is both easily trainable and able to reproduce the long-range temporal dependencies typical of music.
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