An explicit model using learned 3D Gaussians for volume compression encodes geometry explicitly and outperforms implicit neural representations on unstructured volumes with faster training.
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Global 3D hydrodynamical simulations show that a turbulence-driven deflagration-to-detonation transition produces nearly identical peak spectra across diverse ignition densities and topologies in near-Chandrasekhar white dwarfs, matching SN 1999aa.
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Efficient Compression of Structured and Unstructured Volumes via Learned 3D Gaussian Representation
An explicit model using learned 3D Gaussians for volume compression encodes geometry explicitly and outperforms implicit neural representations on unstructured volumes with faster training.