24 citations · 24 across the 3 of their papers we have counts for
3 papers
cs.GR2025
Geometric Integration for Neural Control Variates
Daniel Meister, Takahiro Harada
Control variates are a variance-reduction technique for Monte Carlo integration. The principle involves approximating the integrand by a function that can be analytically integrate…
cs.GR2025
GATE: Geometry-Aware Trained Encoding
Jakub Bokšanský, Daniel Meister, Carsten Benthin
The encoding of input parameters is one of the fundamental building blocks of neural network algorithms. Its goal is to map the input data to a higher-dimensional space, typically…
cs.GR2025★ 24 cited
On Ray Reordering Techniques for Faster GPU Ray Tracing
Daniel Meister, Jakub Bokšanský, Michael Guthe +1
We study ray reordering as a tool for increasing the performance of existing GPU ray tracing implementations. We focus on ray reordering that is fully agnostic to the particular tr…