no code implementations • 10 Sep 2023 • Michalis Vlachos, Mircea Lungu, Yash Raj Shrestha, Johannes-Rudolf David
This is accomplished by identifying content on topics that the user is interested in, and that closely align with the learner's proficiency level in that foreign language.
no code implementations • 1 Feb 2023 • Johannes Schneider, Michalis Vlachos
Deep learning has made tremendous progress in the last decade.
no code implementations • 29 Sep 2021 • Ahmad Ajalloeian, Seyed-Mohsen Moosavi-Dezfooli, Michalis Vlachos, Pascal Frossard
However, a combination of additive and non-additive attacks can still manipulate these explanations, which reveals shortcomings in their robustness properties.
1 code implementation • 27 Nov 2020 • Johannes Schneider, Michalis Vlachos
Humans possess a remarkable capability to make fast, intuitive decisions, but also to self-reflect, i. e., to explain to oneself, and to efficiently learn from explanations by others.
1 code implementation • 27 May 2020 • Johannes Schneider, Michalis Vlachos
We present a `CLAssifier-DECoder' architecture (\emph{ClaDec}) which facilitates the comprehension of the output of an arbitrary layer in a neural network (NN).
no code implementations • 21 Jan 2020 • Johannes Schneider, Christian Meske, Michalis Vlachos
To address this issue, our work investigates how AI models (i. e., deep learning, and existing instruments to increase transparency regarding AI decisions) can be used to create and detect deceptive explanations.