The AI-on-demand platform (AIOD) seeks to act as a resource to facilitate European research and innovation in AI. The objective of the platform is to support all solutions and tools that contribute to the ecosystem of excellence and the ecosystem of trust, which define the European Vision of AI. The AIOD is a community resource […]
Platforms: AI-on-demand Platform Read More »
Julian Schumann at the Insititute for Transportation Studies in Leeds Julian Schumann from TU Delft is one of the students who received funding from TAILOR Connectivity Fund in the last call. Julian presented a project for his PhD period abroad, from TU Delft (TAILOR lab) to the Institute for Transportation Studies at the University of
Report from the Connectivity Fund Read More »
The NeurIPS conference 2022 will be in New Orleans from Monday, November 28th through Friday, December 9th. The NeurIPS conference is one of the major worldwide annual appointments in the field of AI. The conference was founded in 1987 and is now a multi-track interdisciplinary meeting that includes invited talks, demonstrations, symposia, and oral and poster presentations
TAILOR scientists at NeurIPS 2022 Read More »
TAILOR scientists Giuseppe de Giacomo, Fredrik Heintz, Holger Hoos, Ana Paiva, Carles Sierra and Manolis Koubarakis were recently elected Member of the EurAI Board.
6 TAILOR scientists in new EurAI board Read More »
Also for this call, Connectivity Fund received many applications. We are glad to announce the funded projects for this session: For having a look to the other projects granted by Connectivity Fund, check this webpage: https://tailor-network.eu/connectivity-fund/funded-projects/ The next call for Connectivity Fund will be in 4 months. The next deadline is in 15th of March
New projects funded by Connectivity Fund Read More »
Enrico Liscio – TU Delft PhD student Participatory systems aim to elicit citizens’ stances on societal discussions to inform policy making. In particular, human values are a crucial component of citizens’ stances, since they are the drivers of our opinions and behaviors. AI can enable mass participation and process large quantity of citizens’ input. However,
A Modular Framework for Hybrid Participatory Systems Read More »
Julian F. Schumann – TU Delft PhD student For humans to trust autonomous vehicles, they need to have confidence in the vehicles’ ability to reliably resolve space-sharing conflicts with other traffic participants in a safe manner – such as in the case of crossing or merging paths. Planning safe and efficient interactions for autonomous vehicles
Trustworthy AI for human behavior prediction by autonomous vehicles Read More »
Giovanni Franzese – TU Delft PhD candidate The adaptability of robot manipulators to many different tasks is currently constrained by systematic hard coding of each specific task. Recent machine learning methods like Learning from Demonstrations (LfD) and Reinforcement Learning (RL) have shown promising results in having fast reprogramming of the task using human demonstrations or
Graph Gaussian Processes for Interactive Robot Task Learning Read More »
Jeroen G. Rook – University of Twente PhD candidate Comparing algorithms is a non-trivial task. Often, a set of representative problem instances are used to compare algorithms. However, these problem instances introduce biases in the comparison outcomes, which is often not taken into account. The confidence of the comparison can be strengthened by using statistical
Multi-Objective Statistically Robust Algorithm Ranking Read More »
The TAILOR Handbook of Trustworthy AI is an encyclopedia of the major scientific and technical terms related to Trustworthy Artificial Intelligence. The main goal of the Handbook of Trustworthy AI is to provide non experts, especially researchers and students, an overview of the problem related to the development of ethical and trustworthy AI systems. The
TAILOR Handbook of Trustworthy AI Read More »
