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08/24/2023
Match-And-Deform: Time Series Domain Adaptation through Optimal Transport and Temporal Alignment
While large volumes of unlabeled data are usually available, associated ...
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07/04/2023
Fast Optimal Transport through Sliced Wasserstein Generalized Geodesics
Wasserstein distance (WD) and the associated optimal transport plan have...
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06/16/2023
Joint multi-modal Self-Supervised pre-training in Remote Sensing: Application to Methane Source Classification
With the current ubiquity of deep learning methods to solve computer vis...
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06/12/2023
Unbalanced Optimal Transport meets Sliced-Wasserstein
Optimal transport (OT) has emerged as a powerful framework to compare pr...
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05/23/2023
SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities
Many approaches in machine learning rely on a weighted graph to encode t...
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04/06/2023
SALUDA: Surface-based Automotive Lidar Unsupervised Domain Adaptation
Learning models on one labeled dataset that generalize well on another d...
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03/10/2023
Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals
When dealing with electro or magnetoencephalography records, many superv...
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11/18/2022
Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical Projections
It has been shown beneficial for many types of data which present an und...
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09/22/2022
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows
Normalizing Flows (NF) are powerful likelihood-based generative models t...
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06/19/2022
Aligning individual brains with Fused Unbalanced Gromov-Wasserstein
Individual brains vary in both anatomy and functional organization, even...
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06/17/2022
Spherical Sliced-Wasserstein
Many variants of the Wasserstein distance have been introduced to reduce...
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05/31/2022
Template based Graph Neural Network with Optimal Transport Distances
Current Graph Neural Networks (GNN) architectures generally rely on two ...
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05/30/2022
Unbalanced CO-Optimal Transport
Optimal transport (OT) compares probability distributions by computing a...
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02/13/2022
Metric Learning-enhanced Optimal Transport for Biochemical Regression Domain Adaptation
Generalizing knowledge beyond source domains is a crucial prerequisite f...
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10/21/2021
Sliced-Wasserstein Gradient Flows
Minimizing functionals in the space of probability distributions can be ...
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10/21/2021
Subspace Detours Meet Gromov-Wasserstein
In the context of optimal transport methods, the subspace detour approac...
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10/06/2021
Semi-relaxed Gromov Wasserstein divergence with applications on graphs
Comparing structured objects such as graphs is a fundamental operation i...
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10/01/2021
Factored couplings in multi-marginal optimal transport via difference of convex programming
Optimal transport (OT) theory underlies many emerging machine learning (...
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03/05/2021
Unbalanced minibatch Optimal Transport; applications to Domain Adaptation
Optimal transport distances have found many applications in machine lear...
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02/24/2021
Learning to Generate Wasserstein Barycenters
Optimal transport is a notoriously difficult problem to solve numericall...
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02/12/2021
Online Graph Dictionary Learning
Dictionary learning is a key tool for representation learning, that expl...
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01/05/2021
Minibatch optimal transport distances; analysis and applications
Optimal transport distances have become a classic tool to compare probab...
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09/18/2020
Contextual Semantic Interpretability
Convolutional neural networks (CNN) are known to learn an image represen...
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07/13/2020
Representation Transfer by Optimal Transport
Deep learning currently provides the best representations of complex obj...
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04/22/2020
A Cycle GAN Approach for Heterogeneous Domain Adaptation in Land Use Classification
In the field of remote sensing and more specifically in Earth Observatio...
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02/10/2020
Time Series Alignment with Global Invariances
In this work we address the problem of comparing time series while takin...
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02/10/2020
CO-Optimal Transport
Optimal transport (OT) is a powerful geometric and probabilistic tool fo...
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01/27/2020
Generating Natural Adversarial Hyperspectral examples with a modified Wasserstein GAN
Adversarial examples are a hot topic due to their abilities to fool a cl...
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10/09/2019
Learning with minibatch Wasserstein : asymptotic and gradient properties
Optimal transport distances are powerful tools to compare probability di...
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05/24/2019
Sliced Gromov-Wasserstein
Recently used in various machine learning contexts, the Gromov-Wasserste...
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04/08/2019
Pushing the right boundaries matters! Wasserstein Adversarial Training for Label Noise
Noisy labels often occur in vision datasets, especially when they are is...
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01/30/2019
End-to-end Learning for Early Classification of Time Series
Classification of time series is a topical issue in machine learning. Wh...
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11/07/2018
Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties
Optimal transport theory has recently found many applications in machine...
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10/02/2018
An Entropic Optimal Transport Loss for Learning Deep Neural Networks under Label Noise in Remote Sensing Images
Deep neural networks have established as a powerful tool for large scale...
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05/23/2018
Optimal Transport for structured data
Optimal transport has recently gained a lot of interest in the machine l...
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03/27/2018
DeepJDOT: Deep Joint distribution optimal transport for unsupervised domain adaptation
In computer vision, one is often confronted with problems of domain shif...
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03/13/2018
Optimal Transport for Multi-source Domain Adaptation under Target Shift
In this paper, we propose to tackle the problem of reducing discrepancie...
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03/01/2018
Wasserstein Distance Measure Machines
This paper presents a distance-based discriminative framework for learni...
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11/27/2017
Data Dependent Kernel Approximation using Pseudo Random Fourier Features
Kernel methods are powerful and flexible approach to solve many problems...
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11/07/2017
Large-Scale Optimal Transport and Mapping Estimation
This paper presents a novel two-step approach for the fundamental proble...
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10/20/2017
Learning Wasserstein Embeddings
The Wasserstein distance received a lot of attention recently in the com...
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05/24/2017
Joint Distribution Optimal Transportation for Domain Adaptation
This paper deals with the unsupervised domain adaptation problem, where ...
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09/30/2016
Optimal spectral transportation with application to music transcription
Many spectral unmixing methods rely on the non-negative decomposition of...
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08/29/2016
Wasserstein Discriminant Analysis
Wasserstein Discriminant Analysis (WDA) is a new supervised method that ...
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06/23/2016
Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
In this paper, we tackle the question of discovering an effective set of...
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10/22/2015