Rafael Ballester-Ripoll

Rafael Ballester-Ripoll

IE University

H-index: 11

Europe-Spain

About Rafael Ballester-Ripoll

Rafael Ballester-Ripoll, With an exceptional h-index of 11 and a recent h-index of 9 (since 2020), a distinguished researcher at IE University, specializes in the field of tensor decompositions, machine learning, sensitivity analysis, visual computing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Computing Statistical Moments Via Tensorization of Polynomial Chaos Expansions

The YODO algorithm: An efficient computational framework for sensitivity analysis in Bayesian networks

High-dimensional scalar function visualization using principal parameterizations

You only derive once (YODO): automatic differentiation for efficient sensitivity analysis in Bayesian networks

Computing Sobol indices in probabilistic graphical models

Are quantum computers practical yet? a case for feature selection in recommender systems using tensor networks

Tensor approximation of cooperative games and their semivalues

tntorch: Tensor network learning with PyTorch

Rafael Ballester-Ripoll Information

University

Position

School of Human Sciences & Technology

Citations(all)

564

Citations(since 2020)

434

Cited By

269

hIndex(all)

11

hIndex(since 2020)

9

i10Index(all)

12

i10Index(since 2020)

8

Email

University Profile Page

IE University

Google Scholar

View Google Scholar Profile

Rafael Ballester-Ripoll Skills & Research Interests

tensor decompositions

machine learning

sensitivity analysis

visual computing

Top articles of Rafael Ballester-Ripoll

Title

Journal

Author(s)

Publication Date

Computing Statistical Moments Via Tensorization of Polynomial Chaos Expansions

SIAM/ASA Journal on Uncertainty Quantification

Rafael Ballester-Ripoll

2024/6/30

The YODO algorithm: An efficient computational framework for sensitivity analysis in Bayesian networks

International Journal of Approximate Reasoning

Rafael Ballester-Ripoll

Manuele Leonelli

2023/8/1

High-dimensional scalar function visualization using principal parameterizations

The Visual Computer

Rafael Ballester-Ripoll

Gaudenz Halter

Renato Pajarola

2023/6/23

You only derive once (YODO): automatic differentiation for efficient sensitivity analysis in Bayesian networks

Rafael Ballester-Ripoll

Manuele Leonelli

2022/6/17

Computing Sobol indices in probabilistic graphical models

Reliability Engineering & System Safety

Rafael Ballester-Ripoll

Manuele Leonelli

2022/9/1

Are quantum computers practical yet? a case for feature selection in recommender systems using tensor networks

arXiv preprint arXiv:2205.04490

Artyom Nikitin

Andrei Chertkov

Rafael Ballester-Ripoll

Ivan Oseledets

Evgeny Frolov

2022/5/9

Tensor approximation of cooperative games and their semivalues

International Journal of Approximate Reasoning

Rafael Ballester-Ripoll

2022/3/1

tntorch: Tensor network learning with PyTorch

Journal of Machine Learning Research

Mikhail Usvyatsov

Rafael Ballester-Ripoll

Konrad Schindler

2022

SenVis: Interactive Tensor‐based Sensitivity Visualization

Computer Graphics Forum

Haiyan Yang

Rafael Ballester‐Ripoll

Renato Pajarola

2021/6

Cherry-picking gradients: Learning low-rank embeddings of visual data via differentiable cross-approximation

Mikhail Usvyatsov

Anastasia Makarova

Rafael Ballester-Ripoll

Maxim Rakhuba

Andreas Krause

...

2021

Tensor approximation for multidimensional and multivariate data

Renato Pajarola

Susanne K Suter

Rafael Ballester-Ripoll

Haiyan Yang

2021

See List of Professors in Rafael Ballester-Ripoll University(IE University)