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Learning Long-Time Dependencies with RNNs w/ Konstantin Rusch - #484

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

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Challenges and Innovations in RNNs

This chapter explores the difficulties of recurrent neural networks in learning long-term dependencies due to vanishing and exploding gradients. It also introduces the coupled oscillatory RNN architecture inspired by neurobiology, highlighting the balance between controlling parameters and enhancing expressive power.

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