TAILOR is participating in the organisation of a new Challenge! The Challenge is organized by IRT SystemX and the RTE company, with Marc Schoenauer and Sébastien Treguer from Inria contributing to the organization with other researchers, and will be TAILOR representatives for this initiative. This competition aims at promoting the use of ML based surrogate […]
Machine Learning for Physical Simulation Challenge Read More »
The 26th European Conference on Artificial Intelligence ECAI 2023 was held in Krakow from September 30th to October 4th. TAILOR set up a Networking Hub at the conference venue, a space dedicated to meetings and exchanges, which saw the presence of numerous researchers from both our network and other institutions across Europe. Our project manager,
Impressions from ECAI2023 in Krakow: an opportunity to forging connections Read More »
ESSAI is a new yearly event organized under the auspices of the European Association for Artificial Intelligence (EurAI) ESSAI intends to serve as a central hub for PhD students and young researchers working in “all aspects of AI”. The need for such a school emerged in early discussions within CLAIRE and, drawing inspiration from the
ESSAI Summer schools: a longlasting outcome of TAILOR project Read More »
The second cross-cutting Theme Development Workshop (TDW) on “Trusted AI: The Future of Creating Ethical and Responsible AI Systems” was held on 13 September 2023. The TDW was co-organised by all six Networks of AI Excellence (NoE) AI4Media, ELISE, ELSA, euRobin, HumanE-AI-Net, TAILOR together with CLAIRE under the lead of the CSA VISION. The workshop was aimed to develop and identify the most promising and
In July, the ICAPS conference hosted the 10th International Planning Competition (https://ipc2023.github.io/) in Prague. It empirically evaluates state-of-the-art planning systems on a number of benchmark problems. The goals of the IPC are to promote planning research, highlight challenges in the planning community and provide new and interesting problems as benchmarks for future research. The competition
We are thrilled to announce that some TAILOR scientists will participate in one of the most prestigious conferences in the AI field: The European Conference of Artificial Intelligence (ECAI) 2023 in Krakow. ECAI 2023 will feature a full programme of technical papers, as well as many AI-related events of interest for researchers, students and industry
TAILOR Scientists at ECAI 2023 in Krakow Read More »
Congratulations to Wen Chi Yang, Gavin Rens, Giuseppe Marra and Luc De Raedt on winning the IJCAI 2023 Distinguished Paper Award! The IJCAI Distinguished Paper Awards recognise some of the best papers presented at the conference each year. The winners were selected from among more than 4500 papers by the associate programme committee chairs, the programme and general chairs, and the president of EurAI.
IJCAI2023 Distinguished Paper Award to TAILOR Scientists from KU Leuven Read More »
The EU’s six Networks of AI Excellence Centres (NoEs) are providing a Joint Strategic Research Agenda (SRA). The European Union’s aspirations for AI, Data and Robotics (ADR) that are “made in Europe” demand an ambitious approach to advancing European AI research and development. The EU’s six AI Networks of Excellence (NoEs) – AI4Media, ELISE, ELSA, euROBIN, HUMANE-AI-Net, and
The Joint Strategic Research Agenda (SRA): a collaborative effort for the Future of AI Read More »
Matthias könig PhD at Leiden University Abstract: This project seeks to advance the state of the art in formal neural network verification. Formal neural network verification methods check whether a trained neural network, for example an image classifier, satisfies certain properties or guarantees regarding its behaviour, such as correctness, robustness, or safety, under various inputs
Branislav Pecher PhD at Kempelen Institute of Intelligent Technologies, member of Slovak.AI Abstract: Learning with limited labelled data, such as meta-learning, transfer learning or in-context learning, aims to effectively train a model using only a small amount of labelled samples. However, there is still limited understanding of the required settings or characteristics for these approaches
