Rafael Ballester-Ripoll

34 papers A* 1Journal 29Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Global sensitivity analysis of uncertain parameters in Bayesian networks.
Int. J. Approx. Reason.
Rafael Ballester-Ripoll, Manuele Leonelli
2024 J jnl
Computing Statistical Moments Via Tensorization of Polynomial Chaos Expansions.
SIAM/ASA J. Uncertain. Quantification
Rafael Ballester-Ripoll
2024 J jnl
Global Sensitivity Analysis of Uncertain Parameters in Bayesian Networks.
CoRR
Rafael Ballester-Ripoll, Manuele Leonelli
2024 J jnl
High-dimensional scalar function visualization using principal parameterizations.
Vis. Comput.
Rafael Ballester-Ripoll, Gaudenz Halter, Renato Pajarola
2023 J jnl
The YODO algorithm: An efficient computational framework for sensitivity analysis in Bayesian networks.
CoRR
Rafael Ballester-Ripoll, Manuele Leonelli
2023 J jnl
The YODO algorithm: An efficient computational framework for sensitivity analysis in Bayesian networks.
Int. J. Approx. Reason.
Rafael Ballester-Ripoll, Manuele Leonelli
2022 J jnl
Are Quantum Computers Practical Yet? A Case for Feature Selection in Recommender Systems using Tensor Networks.
CoRR
Artyom Nikitin, Andrei Chertkov, Rafael Ballester-Ripoll, Ivan V. Oseledets, Evgeny Frolov
2022 J jnl
Computing Sobol indices in probabilistic graphical models.
Reliab. Eng. Syst. Saf.
Rafael Ballester-Ripoll, Manuele Leonelli
2022 J jnl
T4DT: Tensorizing Time for Learning Temporal 3D Visual Data.
CoRR
Mikhail Usvyatsov, Rafael Ballester-Ripoll, Lina Bashaeva, Konrad Schindler, Gonzalo Ferrer, Ivan V. Oseledets
2022 J jnl
Tensor approximation of cooperative games and their semivalues.
Int. J. Approx. Reason.
Rafael Ballester-Ripoll
2022 — conf
You Only Derive Once (YODO): Automatic Differentiation for Efficient Sensitivity Analysis in Bayesian Networks.
PGM
Rafael Ballester-Ripoll, Manuele Leonelli
2022 J jnl
You Only Derive Once (YODO): Automatic Differentiation for Efficient Sensitivity Analysis in Bayesian Networks.
CoRR
Rafael Ballester-Ripoll, Manuele Leonelli
2022 J jnl
tntorch: Tensor Network Learning with PyTorch.
CoRR
Mikhail Usvyatsov, Rafael Ballester-Ripoll, Konrad Schindler
2022 J jnl
tntorch: Tensor Network Learning with PyTorch.
J. Mach. Learn. Res.
Mikhail Usvyatsov, Rafael Ballester-Ripoll, Konrad Schindler
2021 A* conf
Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation.
ICCV
Mikhail Usvyatsov, Anastasia Makarova, Rafael Ballester-Ripoll, Maxim V. Rakhuba, Andreas Krause, Konrad Schindler
2021 J jnl
Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation.
CoRR
Mikhail Usvyatsov, Anastasia Makarova, Rafael Ballester-Ripoll, Maxim V. Rakhuba, Andreas Krause, Konrad Schindler
2021 J jnl
Global sensitivity analysis in probabilistic graphical models.
CoRR
Rafael Ballester-Ripoll, Manuele Leonelli
2021 J jnl
SenVis: Interactive Tensor-based Sensitivity Visualization.
Comput. Graph. Forum
Haiyan Yang, Rafael Ballester-Ripoll, Renato Pajarola
2020 J jnl
TTHRESH: Tensor Compression for Multidimensional Visual Data.
IEEE Trans. Vis. Comput. Graph.
Rafael Ballester-Ripoll, Peter Lindstrom, Renato Pajarola
2019 J jnl
Sobol tensor trains for global sensitivity analysis.
Reliab. Eng. Syst. Saf.
Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola
2019 J jnl
Tensor Decompositions for Integral Histogram Compression and Look-Up.
IEEE Trans. Vis. Comput. Graph.
Rafael Ballester-Ripoll, Renato Pajarola
2019 — conf
Tensor Methods for Global Sensitivity Analysis.
GI-Jahrestagung
Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola
2019 J jnl
VIAN: A Visual Annotation Tool for Film Analysis.
Comput. Graph. Forum
Gaudenz Halter, Rafael Ballester-Ripoll, Barbara Flückiger, Renato Pajarola
2018 J jnl
Multiresolution Volume Filtering in the Tensor Compressed Domain.
IEEE Trans. Vis. Comput. Graph.
Rafael Ballester-Ripoll, David Steiner, Renato Pajarola
2018 J jnl
TTHRESH: Tensor Compression for Multidimensional Visual Data.
CoRR
Rafael Ballester-Ripoll, Peter Lindstrom, Renato Pajarola
2018 J jnl
Tensor Algorithms for Advanced Sensitivity Metrics.
SIAM/ASA J. Uncertain. Quantification
Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola
2018 J jnl
Visualization of High-dimensional Scalar Functions Using Principal Parameterizations.
CoRR
Rafael Ballester-Ripoll, Renato Pajarola
2017 J jnl
Sobol Tensor Trains for Global Sensitivity Analysis.
CoRR
Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola
2017 J jnl
Tensor Approximation of Advanced Metrics for Sensitivity Analysis.
CoRR
Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola
2016 — conf
A surrogate visualization model using the tensor train format.
SIGGRAPH Asia Symposium on Visualization
Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola
2016 — conf
Compressing Bidirectional Texture Functions via Tensor Train Decomposition.
PG (Short Papers)
Rafael Ballester-Ripoll, Renato Pajarola
2016 J jnl
Lossy volume compression using Tucker truncation and thresholding.
Vis. Comput.
Rafael Ballester-Ripoll, Renato Pajarola
2015 J jnl
Analysis of tensor approximation for compression-domain volume visualization.
Comput. Graph.
Rafael Ballester-Ripoll, Susanne K. Suter, Renato Pajarola
2013 J jnl
Period Selection for Minimal Hyperperiod in Periodic Task Systems.
IEEE Trans. Computers
Ismael Ripoll, Rafael Ballester-Ripoll