Rafael Ballester-Ripoll
Rafael Ballester-Ripoll
School of Science & Technology, IE University
Подтвержден адрес электронной почты в домене ie.edu
TTHRESH: Tensor compression for multidimensional visual data
R Ballester-Ripoll, P Lindstrom, R Pajarola
IEEE Transactions on Visualization and Computer Graphics 26 (9), 2891-2903, 2019
A simulated annealing approach for the joint order batching and order picker routing problem with weight restrictions
EH Grosse, CH Glock, R Ballester-Ripoll
International Journal of Operations and Quantitative Management 20 (2), 65-83, 2014
Sobol tensor trains for global sensitivity analysis
R Ballester-Ripoll, EG Paredes, R Pajarola
Reliability Engineering & System Safety 183, 311-322, 2019
Period selection for minimal hyperperiod in periodic task systems
I Ripoll, R Ballester-Ripoll
IEEE Transactions on Computers 62 (9), 1813-1822, 2012
Lossy volume compression using Tucker truncation and thresholding
R Ballester-Ripoll, R Pajarola
The Visual Computer 32, 1433-1446, 2016
VIAN: A visual annotation tool for film analysis
G Halter, R Ballester‐Ripoll, B Flueckiger, R Pajarola
Computer Graphics Forum 38 (3), 119-129, 2019
Task period selection to minimize hyperperiod
V Brocal, P Balbastre, R Ballester, I Ripoll
IEEE 16th Conference on Emerging Technologies & Factory Automation, 1-4, 2011
Analysis of tensor approximation for compression-domain volume visualization
R Ballester-Ripoll, SK Suter, R Pajarola
Computers & Graphics 47, 34-47, 2015
Morphoproteomic Characterization of Lung Squamous Cell Carcinoma Fragmentation, a Histological Marker of Increased Tumor Invasiveness
R Casanova, D Xia, U Rulle, P Nanni, J Grossmann, B Vrugt, R Wettstein, ...
Cancer Research 77 (10), 2585-2593, 2017
Multiresolution volume filtering in the tensor compressed domain
R Ballester-Ripoll, D Steiner, R Pajarola
IEEE transactions on visualization and computer graphics 24 (10), 2714-2727, 2017
A surrogate visualization model using the tensor train format
R Ballester-Ripoll, EG Paredes, R Pajarola
SIGGRAPH ASIA 2016 Symposium on Visualization, 1-8, 2016
Computing Sobol indices in probabilistic graphical models
R Ballester-Ripoll, M Leonelli
Reliability Engineering & System Safety 225, 108573, 2022
Tensor algorithms for advanced sensitivity metrics
R Ballester-Ripoll, EG Paredes, R Pajarola
SIAM/ASA Journal on Uncertainty Quantification 6 (3), 1172-1197, 2018
tntorch: Tensor network learning with PyTorch
M Usvyatsov, R Ballester-Ripoll, K Schindler
Journal of Machine Learning Research 23 (208), 1-6, 2022
You only derive once (YODO): automatic differentiation for efficient sensitivity analysis in Bayesian networks
R Ballester-Ripoll, M Leonelli
International Conference on Probabilistic Graphical Models, 169-180, 2022
Deep learning tools for foreground-aware analysis of film colors
B Flueckiger, N Evirgen, EG Paredes, R Ballester-Ripoll, R Pajarola
AVinDH SIG, 2017
Are quantum computers practical yet? a case for feature selection in recommender systems using tensor networks
A Nikitin, A Chertkov, R Ballester-Ripoll, I Oseledets, E Frolov
arXiv preprint arXiv:2205.04490, 2022
Cherry-picking gradients: Learning low-rank embeddings of visual data via differentiable cross-approximation
M Usvyatsov, A Makarova, R Ballester-Ripoll, M Rakhuba, A Krause, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
Tensor decompositions for integral histogram compression and look-up
R Ballester-Ripoll, R Pajarola
IEEE Transactions on Visualization and Computer Graphics 25 (2), 1435-1446, 2018
Compressing Bidirectional Texture Functions via Tensor Train Decomposition
R Ballester-Ripoll, R Pajarola
Pacific Graphics Short Papers, 2016
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