ShardTensor is a domain-parallelism system for SciML that enables flexible scaling of extreme-resolution spatial datasets by removing the constraint of batch size one per device.
DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
AeTHERON achieves mean extrapolation MAE of 0.168 while qualitatively capturing vortex topology on unseen timesteps of flapping flexible caudal fin FSI simulations.
citing papers explorer
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ShardTensor: Domain Parallelism for Scientific Machine Learning
ShardTensor is a domain-parallelism system for SciML that enables flexible scaling of extreme-resolution spatial datasets by removing the constraint of batch size one per device.
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AeTHERON: Autoregressive Topology-aware Heterogeneous Graph Operator Network for Fluid-Structure Interaction
AeTHERON achieves mean extrapolation MAE of 0.168 while qualitatively capturing vortex topology on unseen timesteps of flapping flexible caudal fin FSI simulations.