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Found 3 papers, 2 papers with code
L-SeqSleepNet: Whole-cycle Long Sequence Modelling for Automatic Sleep Staging
In this work, we show that while encoding the logic of a whole sleep cycle is crucial to improve sleep staging performance, the sequential modelling approach in existing state-of-the-art deep learning models are inefficient for that purpose.
Optimal State Transfer and Entanglement Generation in Power-law Interacting Systems
We present an optimal protocol for encoding an unknown qubit state into a multiqubit Greenberger-Horne-Zeilinger-like state and, consequently, transferring quantum information in large systems exhibiting power-law ($1/r^\alpha$) interactions.
Quantum Physics Quantum Gases Atomic Physics
XSleepNet: Multi-View Sequential Model for Automatic Sleep Staging
This work proposes a sequence-to-sequence sleep staging model, XSleepNet, that is capable of learning a joint representation from both raw signals and time-frequency images.
Ranked #1 on
Sleep Stage Detection
on PhysioNet Challenge 2018
