5 papers
Toward Scalable and Valid Conditional Independence Testing with Spectral Representations
Alek Fröhlich, Vladimir R. Kostic, Karim Lounici +3
Conditional independence (CI) is central to causal inference, feature selection, and graphical modeling, yet it is untestable in many settings without additional assumptions. Exist…
Geometric implicit neural representations for signed distance functions
Luiz Schirmer, Tiago Novello, VinÃcius da Silva +5
\textit{Implicit neural representations} (INRs) have emerged as a promising framework for representing signals in low-dimensional spaces. This survey reviews the existing literatur…
Adaptive Training of INRs via Pruning and Densification
Diana Aldana, João Paulo Lima, Daniel Csillag +4
Encoding input coordinates with sinusoidal functions into multilayer perceptrons (MLPs) has proven effective for implicit neural representations (INRs) of low-dimensional signals,…
From Volume Rendering to 3D Gaussian Splatting: Theory and Applications
Vitor Pereira Matias, Daniel Perazzo, Vinicius Silva +4
The problem of 3D reconstruction from posed images is undergoing a fundamental transformation, driven by continuous advances in 3D Gaussian Splatting (3DGS). By modeling scenes exp…
FLOWING: Implicit Neural Flows for Structure-Preserving Morphing
Arthur Bizzi, Matias Grynberg, Vitor Matias +7
Morphing is a long-standing problem in vision and computer graphics, requiring a time-dependent warping for feature alignment and a blending for smooth interpolation. Recently, mul…