Explore the words cloud of the DEDALE project. It provides you a very rough idea of what is the project "DEDALE" about.
The following table provides information about the project.
Coordinator |
COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
Organization address contact info |
Coordinator Country | France [FR] |
Project website | http://dedale.cosmostat.org |
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.
# | ||||
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1 | COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES | FR (PARIS 15) | coordinator | 857˙875.00 |
2 | IDRYMA TECHNOLOGIAS KAI EREVNAS | EL (IRAKLEIO) | participant | 560˙000.00 |
3 | TECHNISCHE UNIVERSITAT BERLIN | DE (BERLIN) | participant | 511˙000.00 |
4 | UNIVERSITY COLLEGE LONDON | UK (LONDON) | participant | 485˙397.00 |
5 | SAFRAN ELECTRONICS & DEFENSE | FR (BOULOGNE-BILLANCOURT) | participant | 288˙125.00 |
'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.'
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 |
---|---|---|---|
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: |
2019-04-30 | |
2018 |
Bernard G. Bodmann, Axel Flinth, Gitta Kutyniok Compressed Sensing for Analog Signals published pages: , ISSN: , DOI: |
2019-04-30 | |
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: |
2019-04-30 | |
2018 |
Niall Jeffrey, Filipe B. Abdalla Parameter inference and model comparison using theoretical predictions from noisy simulations published pages: , ISSN: , DOI: |
2019-04-30 | |
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 GarcÃa-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: |
2019-04-30 | |
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: |
2019-04-30 | |
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 ℓ1-Analysis Minimization and Generalized (Co-)Sparsity: When Does Recovery Succeed? published pages: , ISSN: , DOI: |
2019-04-30 | |
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: |
2019-04-30 | |
2017 |
Helmut Bölcskei, Philipp Grohs, Gitta Kutyniok, Philipp Petersen Optimal Approximation with Sparsely Connected Deep Neural Networks published pages: , ISSN: , DOI: |
2019-04-30 | |
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: |
2019-04-30 | |
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: |
2019-04-30 | |
2018 |
Martin Genzel, Gitta Kutyniok The Mismatch Principle: Statistical Learning Under Large Model Uncertainties published pages: , ISSN: , DOI: |
2019-04-30 | |
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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