5 papers
SAMa: Material-aware 3D Selection and Segmentation
Michael Fischer, Iliyan Georgiev, Thibault Groueix +3
Decomposing 3D assets into material parts is a common task for artists, yet remains a highly manual process. In this work, we introduce Select Any Material (SAMa), a material selec…
Canonical correlation analysis of stochastic trends via functional approximation
Massimo Franchi, Iliyan Georgiev, Paolo Paruolo
This paper proposes a novel approach for semiparametric inference on the number of common trends and their loading matrix in systems. It combines functional ap…
Stochastic Ray Tracing of Transparent 3D Gaussians
Xin Sun, Iliyan Georgiev, Yun Fei +1
3D Gaussian splatting has been widely adopted as a 3D representation for novel-view synthesis, relighting, and 3D generation tasks. It delivers realistic and detailed results throu…
Multiple Importance Sampling for Stochastic Gradient Estimation
Corentin Salaün, Xingchang Huang, Iliyan Georgiev +2
We introduce a theoretical and practical framework for efficient importance sampling of mini-batch samples for gradient estimation from single and multiple probability distribution…
Online Importance Sampling for Stochastic Gradient Optimization
Corentin Salaün, Xingchang Huang, Iliyan Georgiev +2
Machine learning optimization often depends on stochastic gradient descent, where the precision of gradient estimation is vital for model performance. Gradients are calculated from…