PHASE: Multi-Regime Modeling of Incompressible Magnetohydrodynamics
cs.LG, physics.comp-ph, physics.plasm-ph
Submitted: 2026-09-29
Updated: 2026-09-29
Sources
- Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators
- DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training
- Poseidon: Efficient Foundation Models for PDEs
- Denoising Diffusion Probabilistic Models
- Project and Generate: Divergence-Free Neural Operators for Incompressible Flows
- Fourier Neural Operator for Parametric Partial Differential Equations
- Multiple Physics Pretraining for Physical Surrogate Models
- Score-Based Generative Modeling through Stochastic Differential Equations
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