25 min listen
Learning Long-Time Dependencies with RNNs w/ Konstantin Rusch - #484
FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Learning Long-Time Dependencies with RNNs w/ Konstantin Rusch - #484
FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
ratings:
Length:
38 minutes
Released:
May 17, 2021
Format:
Podcast episode
Description
Today we conclude our 2021 ICLR coverage joined by Konstantin Rusch, a PhD Student at ETH Zurich. In our conversation with Konstantin, we explore his recent papers, titled coRNN and uniCORNN respectively, which focus on a novel architecture of recurrent neural networks for learning long-time dependencies. We explore the inspiration he drew from neuroscience when tackling this problem, how the performance results compared to networks like LSTMs and others that have been proven to work on this problem and Konstantin’s future research goals. The complete show notes for this episode can be found at twimlai.com/go/484.
Released:
May 17, 2021
Format:
Podcast episode
Titles in the series (100)
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