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CORDIS

Robust Learning and Reasoning for Complex Event Forecasting

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

Ethics Manual on Trustworthy Neuro-symbolic Learning for Complex Event Forecasting (opens in new window)

A report that will a) explain how all data intended to be used for both training and/or validating the project’s techniques and models are relevant, high quality, and limited to the purposes at hand, at both micro and macro level, b) assess whether the neuro-symbolic models and their use in the context of the use cases have any detrimental impact on humans, namely in terms of safety (applicable for all use cases) and contingently discrimination (applicable in use case 2), c) provide adequate information regarding the system's quality, following a risk-based approach and classifying the systems’ risk levels.

Architecture Design and Integrated System Specification (PU version) (opens in new window)

A report on the architecture design, software specifications for the EVENFLOW connectors and best practices towards the development of the integrated prototype.

Data handling, Requirements Analysis & Scenario Definition (opens in new window)

This deliverable will present the data handling process, the requirements analysis and the scenario definitions for the use cases.

Interim Version of Verification and Scalability Techniques (opens in new window)

First version of robustness and efficiency algorithms and tools that support EVENFLOW’s online learning and reasoning approach.

Interim Version of Online Neuro-Symbolic Learning & Reasoning Techniques (opens in new window)

First version of online neuro-symbolic learning and reasoning, explainability and data programming techniques.

Plan for Dissemination and Exploitation Including Communication Activities (opens in new window)

This deliverable will detail the plan for the project dissemination and exploitation strategy to be adopted throughout the project lifetime. Additionally, it will include a report on related projects and actions that EVENFLOW will cooperate with, in order to approach stakeholders.

Interim Use Case Evaluation (opens in new window)

This deliverable will present the results and feedback from the interim evaluation of the tools and the EVENFLOW platform in the three use cases.

Data Management Plan (opens in new window)

A report that will a) provide an overview of the datasets generated and used in the context of the project and the use cases, b) outline how data will be generated and/or collected and processed, subject to all relevant regulations, namely the GDPR, the Data Governance Act and the Proposal for the AI Regulation, c) assess, on top of the methodology and standards to be introduced, whether and how this data will be shared as FAIR and how it will be curated and preserved, in direct alignment with the ethics requirements.

Project Presentation and Website (opens in new window)

This deliverable contains a fact sheet providing an overview of the project, following the EC standards and template, the project presentation and the project website, which will be the main dissemination and exploitation channel for promoting and communicating the project and relevant activities and achievements.

Publications

Nature Communications (opens in new window)

Author(s): Núñez-Carpintero, I; O’Connor, E; Rigau, M; Bosio, M; Spendiff, S; Azuma, Y; Topf, A; Thompson, R; A.C.’t Hoen, P; Chamova, T; Tournev, I; Guergueltcheva, V; Laurie, S; Beltran, S; Capella, S; Cirillo, D; Lochmüller, H; Valencia, A;
Published in: Nature Communications, Issue 15, 2023, ISSN 2041-1723
Publisher: Nature Publishing Group
DOI: 10.1101/2023.01.19.524736,10.1038/s41467-024-45099-0

And synopses for all: A synopses data engine for extreme scale analytics-as-a-service. Information Systems (opens in new window)

Author(s): Antonios Kontaxakis; Nikos Giatrakos; Dimitris Sacharidis; Antonios Deligiannakis
Published in: Information Systems, Issue Volume 116, 2023, ISSN 0306-4379
Publisher: Science Direct
DOI: 10.1016/j.is.2023.102221

From Complexity to Clarity: Evaluating Explainability of Biomedical Machine Learning Models (opens in new window)

Author(s): González Mallo, Marta; Valencia, Alfonso; Cirillo, Davide
Published in: 2024
Publisher: ISMB/ECCB 2023
DOI: 10.5281/zenodo.10564978

Optimizing Resource Allocation for Tumor Simulations over HPC Infrastructures (opens in new window)

Author(s): Streviniotis, Errikos; Giatrakos, Nikos; Kotidis, Yannis; Ntiniakou, Thaleia; Ponce de Leon, Miguel;
Published in: 2023
Publisher: IEEE
DOI: 10.1109/dsaa60987.2023.10302484

Feature Selection via Minimal Covering Sets for Industrial Internet of Things Applications (opens in new window)

Author(s): Christou, Ioannis T.; Soldatos, John; Papadakis, Thanassis; Gutierrez-Rojas, Daniel; Nardelli, Pedro;
Published in: 2023
Publisher: IEEE
DOI: 10.1109/dcoss-iot58021.2023.00092

SSTRESED: Scalable Semantic Trajectory Extraction for Simple Event Detection over Streaming Movement Data (opens in new window)

Author(s): Giatrakos, Nikos
Published in: International Symposium on Temporal Representation and Reasoning (TIME), Issue 30, 2023
Publisher: International Symposium on Temporal Representation and Reasoning (TIME)
DOI: 10.4230/LIPIcs.TIME.2023.15

Answer Set Automata: A Learnable Pattern Specification Framework for Complex Event Recognition (opens in new window)

Author(s): Katzouris, Nikos; Paliouras, Georgios;
Published in: Leibniz International Proceedings in Informatics (LIPIcs), Issue 278, 2023
Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
DOI: 10.4230/LIPIcs.TIME.2023.17

Proactive Streaming Analytics at Scale: A Journey from the State-of-the-art to a Production Platform (opens in new window)

Author(s): Giatrakos, Nikos; Alevizos, Elias; Deligiannakis, Antonios; Kinkenberg, Ralf; Artikis, Alexander
Published in: 2023
Publisher: CIKM ’23
DOI: 10.1145/3583780.3615293

How to Make your Duck Fly: Advanced Floating Point Compression to the Rescue (opens in new window)

Author(s): Liakos, Panagiotis; Papakonstantinopoulou, Katia; Bruineman, Thijs; Raasveldt, Mark; Kotidis, Yannis
Published in: 2024
Publisher: EDBT
DOI: 10.5281/zenodo.10815563

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