Meta-learning aims to leverage the experience from previous tasks to solve new tasks using only little training data, train faster and/or get better performance. The proposed challenge focuses on “cross-domain meta-learning” for few-shot image classification using a novel “any-way” and “any-shot” setting. This challenge is part of TAILOR WP2 (see more information here). Goal The […]
A lot of TAILOR scientists submitted their paperworks to the 31st International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2022). The conference will be in Vienna, from 23rd to 29th of July, 2022. Here below the (not full) list of accepted papers presented by people involved in TAILOR: AISafety
Accepted papers by TAILOR scientists to IJCAI-ECAI 2022 Read More »
IJCAI-ECAI22 is coming up and TAILOR will be there! The conference will be in Vienna, from 23rd to 29th of July, 2022. Two keynotes will be given by TAILOR scientists: Gerhard Widmer (JKU Linz) will talk about “AI & Music: On the Role of AI in Studying a Human Art Form” on Monday 23rd, at 18.00
Keynotes from TAILOR scientists at IJCAI-ECAI 2022 in Vienna Read More »
The “Learning to run a power network challenge 2022” is concerned with AI for smart grids, and it has been built by RTE, the French Power Grid operator, and the TAU team, in collaboration with EPRI, CHA Learn, Google research, UCL and IQT labs.
Learning to Run a Power Network Challenge (L2RPN) Read More »
A paper on learning from a limited data for human body/pose estimation from TAILOR researcher Hossein Rahmani, Lancaster University, has been accepted in the IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR 2022) for oral presentation (acceptance rate is ~4%). This work has been done in collaboration with researchers from Singapore, US and
A TAILOR paper selected for oral presentation at CVPR 2022 Read More »
On 15th of April, TAILOR Connectivity Fund has provided funds for new projects coming from PhD students and researchers from all over Europe. Check the list of all the projects funded by the Connectivity Fund by following this link https://tailor-network.eu/connectivity-fund/funded-projects/. The next deadline for applying to the Connectivity Fund and submitting your project is on
New projects funded by TAILOR Connectivity Fund Read More »
TAILOR researchers Kacper Sokol and Peter Flach have developed a workflow to automatically generate interactive documents, slides and computational notebooks from a collection of markdown source files. The framework offers a novel paradigm in authoring and publishing of scientific outputs. In academia it is quite common to produce multiple variants of the same content published
You Only Write Thrice – a novel AI tool for scientific writing and publishing Read More »
On March 14th 2022, in the context of European AI Week, prof. Freek Bomhof will give the speech “Theme development Workshops: The platform for Academia, Industry & Politics”. The European AI Week is an initiative organized by AI4Belgium ecosystem and its partners, and it will take place from 14th to 18th of March, 2022 in
European AI week: prof. Freek Bomhof on Theme development Workshop Read More »
The TAILOR Network is developing a Strategic Research and Innovation Roadmap (SRIR), with the ambition to define the foundations of Trustworthy AI for the years 2020-2030. This major collaborative effort is now in a pivotal phase, with the first version expected end of March 2022. To continue this work, all TAILOR Network members are encouraged
Contribute to the Roadmap for Trustworthy AI 2020-2030 Read More »
The third Joint Theme Development Workshop (TDW) co-organised by CLAIRE, TAILOR and VISION1 on “AI for Future Healthcare” took place on the 16th December 2021 with the aim to develop and identify the most promising and emerging AI topics in the healthcaresector. At this one-day workshop, experts from academia, industry and politics jointly developed initial
Report from the theme development workshop “AI for future healthcare” Read More »
