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Georgia Institute of Technology
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By explicitly modeling permutation symmetries and geometric attributes, OGPP achieves state-of-the-art generative performance on particle systems with significantly fewer steps and parameters.
Ditch the grid: Free-Range Gaussians synthesizes plausible 3D content from sparse views by predicting non-grid-aligned Gaussians, filling in the blanks where other methods fall apart.
Achieve dramatically wider field of view for UAVs without adding sensors or complexity by simply spinning the entire drone.
Decomposing global transport processes into long-short flow maps offers a new, theoretically grounded approach to understanding and learning drifting models.
