Turstworthy AI for transport-related emission estimation and EU policy making

Andres L. Marin Universitat Politècnica de València Private vehicles have a significant negative impact on the environment, with transport being responsible for more than 20% of energy-related emissions. The EU’s objective is to reduce the emissions of CO2 in 2030 by 55% with respect to 2021. For that reason, a reduction of the emissions from […]

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TAILOR Selected papers: November 2024

Every month, we want to acknowledge some valuable TAILOR papers, selected among the papers published by scientists belonging to our network by TAILOR principal investigator Fredrik Heintz. The list of the most valuable papers gathers contributions from different TAILOR partners, each providing valuable insights on different topics related to TrustworthyAI. This is the very last

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TAILOR Selected papers: October 2024

Every month, we want to acknowledge some valuable TAILOR papers, selected among the papers published by scientists belonging to our network by TAILOR principal investigator Fredrik Heintz.The list of the most valuable papers gathers contributions from different TAILOR partners, each providing valuable insights on different topics related to TrustworthyAI.Stay tuned for other valuable insights and

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TAILOR Selected papers: September 2024

Every month, we want to acknowledge some valuable TAILOR papers, selected among the papers published by scientists belonging to our network by TAILOR principal investigator Fredrik Heintz.The list of the most valuable papers gathers contributions from different TAILOR partners, each providing valuable insights on different topics related to TrustworthyAI.Stay tuned for other valuable insights and

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Learning the structure of complex datasets: The case for simplicial complexes

Antonio G. Marques Professor at King Juan Carlos University Graphs are ubiquitous for modeling the irregular (non-Euclidean) structure of complex data. However, real-world scenarios often involve relationships that span several nodes. While hypergraphs can address such complexities, they lack the mathematical tractability and theoretical foundation of simple graphs. Our strategy for managing these intricate relationships

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Machine Learning for Physical Simulations

IRT-SystemX is a public institute for industrial maturation and transfer, with a long collaboration history with TAILOR partner #3 Inria. IRT-SystemX, together with several academic (including Inria TAU) and industrial (including NVIDIA, RTE and Criteo) partners, organized these Data Challenges to promote the use of Machine Learning-based surrogate models to numerically solve physical problems, through

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TAILOR Selected papers: August 2024

Every month, we want to acknowledge some valuable TAILOR papers, selected among the papers published by scientists belonging to our network by TAILOR principal investigator Fredrik Heintz.The list of the most valuable papers gathers contributions from different TAILOR partners, each providing valuable insights on different topics related to TrustworthyAI.Stay tuned for other valuable insights and

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Exploration of Cooperation Factors in Human-Human and Human-AI InteractionsTiffany Matej Hralovic

Tiffany Matej Hrkalovic PhD Student at Vrije University Amsterdam & Delft University of Technology The enigma of human willingness and ability to cooperate has been a topic of interest for millennia. However, due to the recent technological developments in designing intelligent systems and their potential usage in cooperative settings with humans, newer research is steered

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