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EURECOM
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DrivingVoxels achieves faster and more efficient dynamic scene reconstruction by leveraging independent octrees for rigid objects and a static background, outperforming existing methods in both speed and accuracy.
DIPHINE reveals the intricate information dynamics of complex systems, outperforming traditional methods and enabling insights from real-world data without distributional constraints.
Current evaluation metrics for trajectory inference can mislead researchers, but functional KL divergence offers a clearer, more reliable comparison of methods in sparse data conditions.
