Opendata, web and dolomites


Data Learning on Manifolds and Future Challenges

Total Cost €


EC-Contrib. €






Project "DEDALE" data sheet

The following table provides information about the project.


Organization address
address: RUE LEBLANC 25
city: PARIS 15
postcode: 75015

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country France [FR]
 Project website
 Total cost 2˙702˙397 €
 EC max contribution 2˙702˙397 € (100%)
 Programme 1. H2020-EU.1.2.1. (FET Open)
 Code Call H2020-FETOPEN-2014-2015-RIA
 Funding Scheme RIA
 Starting year 2015
 Duration (year-month-day) from 2015-10-01   to  2018-09-30


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
4    UNIVERSITY COLLEGE LONDON UK (LONDON) participant 485˙397.00


 Project objective

'Future data processing challenges in science will enter the 'Big Data' era, involving massive, as well as complex and heterogeneous data. Extracting, with high precision, every bit of information from scientific data requires overcoming fundamental statistical challenges, which mandate the design of dedicated methods that must be both effective enough to capture the intricacy of real-world datasets and robust to the high complexity of instrumental measurements. Moreover, future datasets, such as those provided by the space mission Euclid, will involve at least gigascale data, which will make mandatory the development of new, physically relevant, data models and the implementation of effective and computationally efficient processing tools. The recent emergence of novel data analysis methods in machine learning should foster a new modeling framework, allowing for a better preservation of the intrinsic physical properties of real data that generally live on intricate spaces, such as signal manifolds. Furthermore, advances in operations research and optimization theory pave the way for effective solutions to overcome the large-scale data processing bottlenecks. In this context, the objective of the DEDALE project is threefold: i) introduce new models and methods to analyze and restore complex, multivariate, manifold-based signals; ii) exploit the current knowledge in optimization and operations research to build efficient numerical data processing algorithms in the large-scale settings; and iii) show the reliability of the proposed data modeling and analysis technologies to tackle Scientific Big Data challenges in two different applications: one in cosmology, to map the dark matter mass map of the universe, and one in remote sensing to increase the capabilities of automatic airborne imaging analysis systems.'


List of deliverables.
Numerical toolbox and benchmarking platform. Demonstrators, pilots, prototypes 2019-04-30 11:35:25
Optimizations for non-linear learning. Documents, reports 2019-04-30 11:35:25
Dictionary learning for multivariate/multispectral data. Documents, reports 2019-04-30 11:35:25
Super-resolution and interpolation of the Euclid PSF Documents, reports 2019-04-30 11:35:25
Toolbox and benchmarking platform for large scale learning. Demonstrators, pilots, prototypes 2019-04-30 11:35:25
Optimization for manifold-valued signal restoration. Documents, reports 2019-04-30 11:35:25
Non-linear learning on complex imaging data. Documents, reports 2019-04-30 11:35:25
Evaluation/validation of the mass mapping algorithms Open Research Data Pilot 2019-04-30 11:35:24
Linear inverse problems with sparsity constraints. Documents, reports 2019-05-30 11:42:35
Large-scale learning schemes. Documents, reports 2019-05-30 11:42:48
Adaptive transforms for manifold-valued data. Documents, reports 2019-05-30 11:42:46
Learning-based photometric and spectroscopic redshift estimation Documents, reports 2019-05-30 11:42:44
Project Website & Factsheet Websites, patent fillings, videos etc. 2019-05-30 11:42:46

Take a look to the deliverables list in detail:  detailed list of DEDALE deliverables.


year authors and title journal last update
List of publications.
2017 Sofia Savvaki, Grigorios Tsagkatakis, Athanasia Panousopoulou, Panagiotis Tsakalides
Matrix and Tensor Completion on a Human Activity Recognition Framework
published pages: 1554-1561, ISSN: 2168-2194, DOI: 10.1109/JBHI.2017.2716112
IEEE Journal of Biomedical and Health Informatics 21/6 2019-04-30
2018 Philipp Petersen, Felix Voigtlaender
Optimal approximation of piecewise smooth functions using deep ReLU neural networks
published pages: 296-330, ISSN: 0893-6080, DOI: 10.1016/j.neunet.2018.08.019
Neural Networks 108 2019-04-30
2017 J. Frontera-Pons, F. Sureau, J. Bobin, E. Le Floc’h
Unsupervised feature-learning for galaxy SEDs with denoising autoencoders
published pages: A60, ISSN: 0004-6361, DOI: 10.1051/0004-6361/201630240
Astronomy & Astrophysics 603 2019-04-30
2017 Sandra Keiper, Gitta Kutyniok, Dae Gwan Lee, Götz E. Pfander
Compressed sensing for finite-valued signals
published pages: 570-613, ISSN: 0024-3795, DOI: 10.1016/j.laa.2017.07.006
Linear Algebra and its Applications 532 2019-04-30
2018 Morgan A. Schmitz, Matthieu Heitz, Nicolas Bonneel, Fred Ngolè, David Coeurjolly, Marco Cuturi, Gabriel Peyré, Jean-Luc Starck
Wasserstein Dictionary Learning: Optimal Transport-Based Unsupervised Nonlinear Dictionary Learning
published pages: 643-678, ISSN: 1936-4954, DOI: 10.1137/17M1140431
SIAM Journal on Imaging Sciences 11/1 2019-04-30
2018 Rafael Reisenhofer, Sebastian Bosse, Gitta Kutyniok, Thomas Wiegand
A Haar wavelet-based perceptual similarity index for image quality assessment
published pages: 33-43, ISSN: 0923-5965, DOI: 10.1016/j.image.2017.11.001
Signal Processing: Image Communication 61 2019-04-30
2017 Martin Genzel, Peter Jung
Recovering Structured Data From Superimposed Non-Linear Measurements
published pages: , ISSN: , DOI:
2018 Bernard G. Bodmann, Axel Flinth, Gitta Kutyniok
Compressed Sensing for Analog Signals
published pages: , ISSN: , DOI:
2015 Grohs, Philipp; Kutyniok, Gitta; Ma, Jackie; Petersen, Philipp; Raslan, Mones
Anisotropic Multiscale Systems on Bounded Domains
published pages: , ISSN: , DOI:
33 2019-04-30
2018 Radamanthys Stivaktakis, Grigorios Tsagkatakis, Bruno Moraes, Filipe Abdalla, Jean-Luc Starck, Panagiotis Tsakalides
Convolutional Neural Networks for Spectroscopic Redshift Estimation on Euclid Data
published pages: , ISSN: , DOI:
2018 Niall Jeffrey, Filipe B. Abdalla
Parameter inference and model comparison using theoretical predictions from noisy simulations
published pages: , ISSN: , DOI:
2018 N Jeffrey, F B Abdalla, O Lahav, F Lanusse, J-L Starck, A Leonard, D Kirk, C Chang, E Baxter, T Kacprzak, S Seitz, V Vikram, L Whiteway, T M C Abbott, S Allam, S Avila, E Bertin, D Brooks, A Carnero Rosell, M Carrasco Kind, J Carretero, F J Castander, M Crocce, C E Cunha, C B D’Andrea, L N da Costa, C Davis, J De Vicente, S Desai, P Doel, T F Eifler, A E Evrard, B Flaugher, P Fosalba, J Frieman, J García-Bellido, D W Gerdes, D Gruen, R A Gruendl, J Gschwend, G Gutierrez, W G Hartley, K Honscheid, B Hoyle, D J James, M Jarvis, K Kuehn, M Lima, H Lin, M March, P Melchior, F Menanteau, R Miquel, A A Plazas, K Reil, A Roodman, E Sanchez, V Scarpine, M Schubnell, I Sevilla-Noarbe, M Smith, M Soares-Santos, F Sobreira, E Suchyta, M E C Swanson, G Tarle, D Thomas, A R Walker
Improving weak lensing mass map reconstructions using Gaussian and sparsity priors: application to DES SV
published pages: 2871-2888, ISSN: 0035-8711, DOI: 10.1093/mnras/sty1252
Monthly Notices of the Royal Astronomical Society 479/3 2019-04-30
2017 Felix Voigtlaender, Anne Pein
Analysis vs. synthesis sparsity for α-shearlets
published pages: , ISSN: , DOI:
2016 F Ngolè, J-L Starck, K Okumura, J Amiaux, P Hudelot
Constraint matrix factorization for space variant PSFs field restoration
published pages: 124001, ISSN: 0266-5611, DOI: 10.1088/0266-5611/32/12/124001
Inverse Problems 32/12 2019-04-30
2016 Genzel, Martin; Kutyniok, Gitta
A Mathematical Framework for Feature Selection from Real-World Data with Non-Linear Observations
published pages: , ISSN: , DOI:
25 2019-04-30
2016 Voigtlaender, Felix
Structured, compactly supported Banach frame decompositions of decomposition spaces
published pages: , ISSN: , DOI:
21 2019-04-30
2018 Martin Genzel, Alexander Stollenwerk
Robust 1-Bit Compressed Sensing via Hinge Loss Minimization
published pages: , ISSN: , DOI:
2018 J D Rivera, B Moraes, A I Merson, S Jouvel, F B Abdalla, M C B Abdalla
Degradation analysis in the estimation of photometric redshifts from non-representative training sets
published pages: 4330-4347, ISSN: 0035-8711, DOI: 10.1093/mnras/sty880
Monthly Notices of the Royal Astronomical Society 477/4 2019-04-30
2017 Martin Genzel, Gitta Kutyniok, Maximilian März
â„“1-Analysis Minimization and Generalized (Co-)Sparsity: When Does Recovery Succeed?
published pages: , ISSN: , DOI:
2018 A. Panousopoulou, S. Farrens, K. Fotiadou, A. Woiselle, G. Tsagkatakis, , J.-L. Starck, P. Tsakalides
A Distributed Learning Architecture for Scientific Imaging Problems
published pages: , ISSN: , DOI:
2017 Helmut Bölcskei, Philipp Grohs, Gitta Kutyniok, Philipp Petersen
Optimal Approximation with Sparsely Connected Deep Neural Networks
published pages: , ISSN: , DOI:
2018 Arthur Loureiro, Bruno Moraes, Filipe B. Abdalla, Andrei Cuceu, Michael McLeod, Lorne Whiteway, Sreekumar T. Balan, Aurélien Benoit-Lévy, Ofer Lahav, Marc Manera, Richard Rollins, Henrique S. Xavier
ZXCorr: Cosmological Measurements from Angular Power Spectra Analysis of BOSS DR12 Tomography
published pages: , ISSN: , DOI:
2017 Austin Peel, Chieh-An Lin, François Lanusse, Adrienne Leonard, Jean-Luc Starck, Martin Kilbinger
Cosmological constraints with weak-lensing peak counts and second-order statistics in a large-field survey
published pages: A79, ISSN: 0004-6361, DOI: 10.1051/0004-6361/201629928
Astronomy & Astrophysics 599 2019-04-30
2018 Austin Peel, Valeria Pettorino, Carlo Giocoli, Jean-Luc Starck, Marco Baldi
Breaking degeneracies in modified gravity with higher (than 2nd) order weak-lensing statistics
published pages: A38, ISSN: 0004-6361, DOI: 10.1051/0004-6361/201833481
Astronomy & Astrophysics 619 2019-04-30
2018 Florent Sureau, Felix Voigtlaender, Malte Wust, Jean-Luc Starck, Gitta Kutyniok
Learning sparse representations on the sphere
published pages: , ISSN: , DOI:
2018 Martin Genzel, Gitta Kutyniok
The Mismatch Principle: Statistical Learning Under Large Model Uncertainties
published pages: , ISSN: , DOI:
2017 S. Farrens, F. M. Ngolè Mboula, J.-L. Starck
Space variant deconvolution of galaxy survey images
published pages: A66, ISSN: 0004-6361, DOI: 10.1051/0004-6361/201629709
Astronomy & Astrophysics 601 2019-04-30
2016 J. Bobin, F. Sureau, J.-L. Starck
Cosmic microwave background reconstruction from WMAP and Planck PR2 data
published pages: A50, ISSN: 0004-6361, DOI: 10.1051/0004-6361/201527822
Astronomy & Astrophysics 591 2019-04-30
2017 Austin Peel, François Lanusse, Jean-Luc Starck
Sparse Reconstruction of the Merging A520 Cluster System
published pages: 23, ISSN: 1538-4357, DOI: 10.3847/1538-4357/aa850d
The Astrophysical Journal 847/1 2019-04-30
2016 Philipp Grohs, Sandra Keiper, Gitta Kutyniok, Martin Schäfer
α -Molecules
published pages: 297-336, ISSN: 1063-5203, DOI: 10.1016/j.acha.2015.10.009
Applied and Computational Harmonic Analysis 41/1 2019-04-30
2016 Konstantinos Karalas, Grigorios Tsagkatakis, Michael Zervakis, Panagiotis Tsakalides
Land Classification Using Remotely Sensed Data: Going Multilabel
published pages: 3548-3563, ISSN: 0196-2892, DOI: 10.1109/TGRS.2016.2520203
IEEE Transactions on Geoscience and Remote Sensing 54/6 2019-04-30
2016 R. Joseph, F. Courbin, J.-L. Starck
Multi-band morpho-Spectral Component Analysis Deblending Tool (MuSCADeT): Deblending colourful objects
published pages: A2, ISSN: 0004-6361, DOI: 10.1051/0004-6361/201527923
Astronomy & Astrophysics 589 2019-04-30
2016 Jean-Luc Starck
Sparsity and inverse problems in astrophysics
published pages: 12010, ISSN: 1742-6588, DOI: 10.1088/1742-6596/699/1/012010
Journal of Physics: Conference Series 699 2019-04-30
2016 F. Lanusse, J.-L. Starck, A. Leonard, S. Pires
High resolution weak lensing mass mapping combining shear and flexion
published pages: A2, ISSN: 0004-6361, DOI: 10.1051/0004-6361/201628278
Astronomy & Astrophysics 591 2019-04-30
2016 Grigorios Tsagkatakis, Baltasar Beferull-Lozano, Panagiotis Tsakalides
Singular spectrum-based matrix completion for time series recovery and prediction
published pages: , ISSN: 1687-6180, DOI: 10.1186/s13634-016-0360-0
EURASIP Journal on Advances in Signal Processing 2016/1 2019-04-30
2017 F. Ngolé, J.-L. Starck
Point Spread Function Field Learning Based on Optimal Transport Distances
published pages: 1549-1578, ISSN: 1936-4954, DOI: 10.1137/16M1093677
SIAM Journal on Imaging Sciences 10/3 2019-04-30

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