CORDIS provides links to public deliverables and publications of HORIZON projects.
Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .
Deliverables
Initial report about the main theoretical results and comparison between the different Deep PDE solvers.
Baseline model for PDE enhancement with collected data. (opens in new window)Characterization of the techniques developed to enrich PDEs utilizing available data.
Datasets requirements for parametric PDEs. (opens in new window)Generation, analysis, and sampling of the dataset in parametric PDEs.
Gender and diversity equality plan. (opens in new window)Priorities, concrete objectives, and the specific measures that will be implemented to improve gender and diversity equality within the IN-DEEP project.
Training events in M1-24 (opens in new window)Description and self-assessment of training events and proposed correction measures.
Computational complexity control through adaptive strategies in Deep PDE solvers for parametric problems. (opens in new window)Efficiency assessment of the novel adaptive strategies developed for Deep PDE solvers applied to parametric problems.
Optimization techniques for Deep PDE solvers. (opens in new window)Analysis of the effect of adaptive strategies on the algorithms.
Advances in theory and numerical approximation of Deep PDE solvers for parametric problems. (opens in new window)Initial Analytical study and partial numerical validation of the proposed methodology. Comparison with conventional solvers.
Loss function choice criteria, according to the PDE problem. (opens in new window)Study of the appropriateness and efficiency of the loss function in Deep PDE solvers. Advantages, limitations, recommendations for forward, inverse, and parametric problems.
Project website, logo and social media page creation
Publications
Author(s):
Magdalena Pabisz, Dominika Ciupek, Askold Vilkha, Maciej Paszyński
Published in:
Lecture Notes in Computer Science, Computational Science – ICCS 2025 Workshops, 2025, ISBN 978-3-031-97554-7
Publisher:
Springer Nature Switzerland
DOI:
10.1007/978-3-031-97554-7_10
Author(s):
Askold Vilkha, Carlos Uriarte, Paweł Maczuga, Tomasz Służalec, Maciej Paszyński
Published in:
Lecture Notes in Computer Science, Computational Science – ICCS 2025, 2025, ISBN 978-3-031-97626-1
Publisher:
Springer Nature Switzerland
DOI:
10.1007/978-3-031-97626-1_5
Author(s):
Marcin Łoś, Tomasz Służalec, Paweł Maczuga, Askold Vilkha, Carlos Uriarte, Maciej Paszyński
Published in:
Computers & Structures, Issue 316, 2025, ISSN 0045-7949
Publisher:
Elsevier BV
DOI:
10.1016/J.COMPSTRUC.2025.107839
Author(s):
Shima Baharlouei; Jamie M. Taylor; Carlos Uriarte; David Pardo
Published in:
Computer Methods in Applied Mechanics and Engineering, 2024, ISSN 0045-7825
Publisher:
Elsevier BV
DOI:
10.2139/SSRN.5004047
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