activity
20242026
most citedOn the Performance and Implementation of Parallax free Video See-Through Displays

8 citations · 8 across the 4 of their papers we have counts for

collaborators

7 papers

stat.ML2026

Variational Low-rank Tensor Decomposition for Multisubject Spatiotemporal Data Analysis

Laura M. Montaldo, Ricardo A. Borsoi, Sebastian Miron +1

Modeling shared and subject-specific structure in multisubject spatiotemporal data remains challenging, particularly in neuroimaging, where both spatial and temporal patterns exhib…

cs.GR20268 cited

On the Performance and Implementation of Parallax free Video See-Through Displays

Ricardo Augusto Borsoi, Guilherme Holsbach Costa

In see-through systems an observer watches a (background) scene partially occluded by a display. In this display, usually positioned close to the observer, a region of the backgrou…

eess.IV2026

Group-invariant Coresets for Data-efficient Active Learning

L. C. Ayres, J. C. M. Bermudez, S. J. M. de Almeida +1

Active learning reduces labeling cost by querying the most informative unlabeled samples, but standard coreset methods ignore known data symmetries and can waste budget on transfor…

eess.SP2026

Distributed Riemannian Optimization in Geodesically Non-convex Environments

Xiuheng Wang, Ricardo Borsoi, Cédric Richard +1

This paper studies the problem of distributed Riemannian optimization over a network of agents whose cost functions are geodesically smooth but possibly geodesically non-convex. Ex…

eess.IV2025

Robust Recursive Fusion of Multiresolution Multispectral Images with Location-Aware Neural Networks

Haoqing Li, Ricardo Borsoi, Tales Imbiriba +1

Multiresolution image fusion is a key problem for real-time satellite imaging and plays a central role in detecting and monitoring natural phenomena such as floods. It aims to solv…

cs.LG2025

Riemannian Change Point Detection on Manifolds with Robust Centroid Estimation

Xiuheng Wang, Ricardo Borsoi, Arnaud Breloy +1

Non-parametric change-point detection in streaming time series data is a long-standing challenge in signal processing. Recent advancements in statistics and machine learning have i…