Checkpoints of the models benchmarked on the Well in the original paper.

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We usher in a new class of machine learning for scientific data, building models that can leverage shared concepts across disciplines. We aim to develop, train, and release such foundation models for use by researchers worldwide.
Collections
2
models
62

polymathic-ai/UNetClassic-viscoelastic_instability
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polymathic-ai/UNetClassic-turbulence_gravity_cooling
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polymathic-ai/UNetClassic-supernova_explosion_64
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2

polymathic-ai/UNetClassic-shear_flow
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polymathic-ai/UNetClassic-rayleigh_taylor_instability
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2

polymathic-ai/UNetClassic-rayleigh_benard
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polymathic-ai/UNetClassic-planetswe
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3

polymathic-ai/UNetClassic-MHD_64
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polymathic-ai/UNetClassic-helmholtz_staircase
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polymathic-ai/UNetClassic-gray_scott_reaction_diffusion
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3
datasets
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polymathic-ai/acoustic_scattering_discontinuous
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112
polymathic-ai/gray_scott_reaction_diffusion
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294
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polymathic-ai/turbulence_gravity_cooling
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446
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1
polymathic-ai/rayleigh_taylor_instability
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288
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polymathic-ai/planetswe
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187
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1
polymathic-ai/convective_envelope_rsg
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215
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1
polymathic-ai/MHD_64
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67
polymathic-ai/viscoelastic_instability
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81
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polymathic-ai/turbulent_radiative_layer_2D
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69
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1
polymathic-ai/shear_flow
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1