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20222026
most citedReduced Order Modeling with Shallow Recurrent Decoder Networks

13 citations · 27 across the 10 of their papers we have counts for

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7 papers · 1 filter

cs.LG2026

CTF4Nuclear: Common Task Framework for Nuclear Fission and Fusion Models

Stefano Riva, Carolina Introini, Antonio Cammi +13

The demand for clean energy is ever increasing, with new nuclear technologies presenting a complementary solution to renewable energies. However, designing and operating these syst…

cs.LG2026

OpenReservoirComputing: GPU-Accelerated Reservoir Computing in JAX

Jan Williams, Dima Tretiak, Steven L. Brunton +2

OpenReservoirComputing (ORC) is a Python library for reservoir computing (RC) written in JAX (Bradbury et al. 2018) and Equinox (Kidger and Garcia 2021). JAX is a Python library fo…

cs.LG2025

The Seismic Wavefield Common Task Framework

Alexey Yermakov, Yue Zhao, Marine Denolle +13

Seismology faces fundamental challenges in state forecasting and reconstruction (e.g., earthquake early warning and ground motion prediction) and managing the parametric variabilit…

cs.LG2025

PySHRED: A Python package for SHallow REcurrent Decoding for sparse sensing, model reduction and scientific discovery

David Ye, Jan Williams, Mars Gao +4

SHallow REcurrent Decoders (SHRED) provide a deep learning strategy for modeling high-dimensional dynamical systems and/or spatiotemporal data from dynamical system snapshot observ…

cs.LG2025★ 13 cited

Reduced Order Modeling with Shallow Recurrent Decoder Networks

Matteo Tomasetto, Jan P. Williams, Francesco Braghin +2

Reduced Order Modeling is of paramount importance for efficiently inferring high-dimensional spatio-temporal fields in parametric contexts, enabling computationally tractable param…

cs.LG2025

Sparse identification of nonlinear dynamics and Koopman operators with Shallow Recurrent Decoder Networks

Mars Liyao Gao, Jan P. Williams, J. Nathan Kutz

Modeling real-world spatio-temporal data is exceptionally difficult due to inherent high dimensionality, measurement noise, partial observations, and often expensive data collectio…

cs.LG2023★ 3 cited

Leveraging arbitrary mobile sensor trajectories with shallow recurrent decoder networks for full-state reconstruction

Megan R. Ebers, Jan P. Williams, Katherine M. Steele +1

Sensing is one of the most fundamental tasks for the monitoring, forecasting and control of complex, spatio-temporal systems. In many applications, a limited number of sensors are…