activity
20112021
most citedTTHRESH: Tensor Compression for Multidimensional Visual Data

176 citations · 184 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV2021

Walk2Map: Extracting Floor Plans from Indoor Walk Trajectories

Claudio Mura, Renato Pajarola, Konrad Schindler +1

Recent years have seen a proliferation of new digital products for the efficient management of indoor spaces, with important applications like emergency management, virtual propert…

cs.GR2019★ 7 cited

LOCALIS: Locally-adaptive Line Simplification for GPU-based Geographic Vector Data Visualization

Alireza Amiraghdam, Alexandra Diehl, Renato Pajarola

Visualization of large vector line data is a core task in geographic and cartographic systems. Vector maps are often displayed at different cartographic generalization levels, trad…

cs.GR2018★ 1 cited

Visualization of High-dimensional Scalar Functions Using Principal Parameterizations

Rafael Ballester-Ripoll, Renato Pajarola

Insightful visualization of multidimensional scalar fields, in particular parameter spaces, is key to many fields in computational science and engineering. We propose a principal c…

cs.GR2018★ 176 cited

TTHRESH: Tensor Compression for Multidimensional Visual Data

Rafael Ballester-Ripoll, Peter Lindstrom, Renato Pajarola

Memory and network bandwidth are decisive bottlenecks when handling high-resolution multidimensional data sets in visualization applications, and they increasingly demand suitable…

cs.GR2018

Equalizer 2.0 - Convergence of a Parallel Rendering Framework

Stefan Eilemann, David Steiner, Renato Pajarola

Developing complex, real world graphics applications which leverage multiple GPUs and computers for interactive 3D rendering tasks is a complex task. It requires expertise in distr…

math.NA2017

Tensor Approximation of Advanced Metrics for Sensitivity Analysis

Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola

Following up on the success of the analysis of variance (ANOVA) decomposition and the Sobol indices (SI) for global sensitivity analysis, various related quantities of interest hav…

math.NA2017

Sobol Tensor Trains for Global Sensitivity Analysis

Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola

Sobol indices are a widespread quantitative measure for variance-based global sensitivity analysis, but computing and utilizing them remains challenging for high-dimensional system…

physics.ed-ph2012

Visualizing Flat Spacetime: Viewing Optical versus Special Relativistic Effects

Don V. Black, M. Gopi, F. Wessel +2

A simple visual representation of Minkowski spacetime appropriate for a student with a background in geometry and algebra is presented. Minkowski spacetime can be modeled with a Eu…

math.NA2011

On best rank one approximation of tensors

S. Friedland, V. Mehrmann, R. Pajarola +1

In this paper we suggest a new algorithm for the computation of a best rank one approximation of tensors, called alternating singular value decomposition. This method is based on t…