5 papers
Autoregressive long-horizon prediction of plasma edge dynamics
Hunor Csala, Sebastian De Pascuale, Paul Laiu +3
Accurate modeling of scrape-off layer (SOL) and divertor-edge dynamics is vital for designing plasma-facing components in fusion devices. High-fidelity edge fluid/neutral codes suc…
Intelligent Sampling of Extreme-Scale Turbulence Datasets for Accurate and Efficient Spatiotemporal Model Training
Wesley Brewer, Murali Meena Gopalakrishnan, Matthias Maiterth +12
With the end of Moore's law and Dennard scaling, efficient training increasingly requires rethinking data volume. Can we train better models with significantly less data via intell…
Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit
Junqi Yin, Mijanur Palash, M. Paul Laiu +6
Turbulence plays a crucial role in multiphysics applications, including aerodynamics, fusion, and combustion. Accurately capturing turbulence's multiscale characteristics is essent…
A Separable Self-attention Inspired by the State Space Model for Computer Vision
Juntao Zhang, Shaogeng Liu, Kun Bian +5
Mamba is an efficient State Space Model (SSM) with linear computational complexity. Although SSMs are not suitable for handling non-causal data, Vision Mamba (ViM) methods still de…
Falcon: Fractional Alternating Cut with Overcoming Minima in Unsupervised Segmentation
Xiao Zhang, Xiangyu Han, Xiwen Lai +3
Today's unsupervised image segmentation algorithms often segment suboptimally. Modern graph-cut based approaches rely on high-dimensional attention maps from Transformer-based foun…