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Learning Long-Time Dependencies with RNNs w/ Konstantin Rusch - #484
b'Today we conclude our 2021 ICLR coverage joined by Konstantin Rusch, a PhD Student at ETH Zurich.\\nIn 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.\\nWe 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\\u2019s future research goals.\\nThe complete show notes for this episode can be found at twimlai.com/go/484.'