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Parallel-in-Time Training of Recurrent Neural Networks for Dynamical Systems Reconstruction

DEER with generalized teacher forcing trains recurrent networks in parallel time to learn nonlinear dynamics on long sequences, outperforming linear state-space models for systems with long time scales.

Florian Hess, Florian Götz, Daniel Durstewitz

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 1 on Hugging Face

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AI panel: 9 of 20 reviewers recommend it
lenient 3/5
medium 6/10
strict 0/5