677 citations
- Université de Rouen NormandieFR107 papers
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14 papers · 1 filter
Random Forest Kernel for High-Dimension Low Sample Size Classification
Lucca Portes Cavalheiro, Simon Bernard, Jean Paul Barddal +1
High dimension, low sample size (HDLSS) problems are numerous among real-world applications of machine learning. From medical images to text processing, traditional machine learnin…
Learning with minibatch Wasserstein : asymptotic and gradient properties
Kilian Fatras, Younes Zine, Rémi Flamary +2
Optimal transport distances are powerful tools to compare probability distributions and have found many applications in machine learning. Yet their algorithmic complexity prevents…
Screening Sinkhorn Algorithm for Regularized Optimal Transport
Mokhtar Z. Alaya, Maxime Bérar, Gilles Gasso +1
We introduce in this paper a novel strategy for efficiently approximating the Sinkhorn distance between two discrete measures. After identifying neglectable components of the dual…
Large-Scale Optimal Transport and Mapping Estimation
Vivien Seguy, Bharath Bhushan Damodaran, Rémi Flamary +3
This paper presents a novel two-step approach for the fundamental problem of learning an optimal map from one distribution to another. First, we learn an optimal transport (OT) pla…
Inversion using a new low-dimensional representation of complex binary geological media based on a deep neural network
Eric Laloy, Romain Hérault, John Lee +2
Efficient and high-fidelity prior sampling and inversion for complex geological media is still a largely unsolved challenge. Here, we use a deep neural network of the variational a…
Training-image based geostatistical inversion using a spatial generative adversarial neural network
Eric Laloy, Romain Hérault, Diederik Jacques +1
Probabilistic inversion within a multiple-point statistics framework is often computationally prohibitive for high-dimensional problems. To partly address this, we introduce and ev…