Physics-Integrated Operator Learning via Gaussian Splatting Representations
cs.LG
Submitted: 2026-08-25
Updated: 2026-08-25
Terminology
Sources
- Neural Operator: Learning Maps Between Function Spaces
- FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
- PDEBENCH: An Extensive Benchmark for Scientific Machine Learning
- Physics-Informed Neural Operator for Learning Partial Differential Equations
- INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation
- Group Equivariant Fourier Neural Operators for Partial Differential Equations
- Neural Operators with Localized Integral and Differential Kernels
- From Basis to Basis: Gaussian Particle Representation for Interpretable PDE Operators
- Gaussian Fluids: A Grid-Free Fluid Solver based on Gaussian Spatial Representation
- pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction
- VolSplat: Rethinking Feed-Forward 3D Gaussian Splatting with Voxel-Aligned Prediction
- SparseSplat: Towards Applicable Feed-Forward 3D Gaussian Splatting with Pixel-Unaligned Prediction
- FLUIDSPLAT: Reconstructing Physical Fields from Sparse Sensors via Gaussian Primitives
- Fourier Neural Operator for Parametric Partial Differential Equations
- U-Net: Convolutional Networks for Biomedical Image Segmentation
- Deep Residual Learning for Image Recognition
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