Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
I-2503 – PHD IN EXPLAINABLE AI FOR DATA-DRIVEN PHYSIOLOGICAL AND BEHAVIORAL MODELLING OF CAR DRIVERS
, data-science (e.g., neural networks, deep learning, autoencoders, GANs, active learning, etc.); · Knowledge of explainable AI and Knowledge Graphs with ontology (e.g., RDFS, OWL
-
LevelMaster Degree or equivalent Skills/Qualifications Candidates should be able to demonstrate hands-on experience with deep-learning, graph neural networks, computer vision and associated development tools
-
best stability? Ultimately, the PhD candidate will develop a neural network to identify specific properties/processing conditions/device layouts that are key determinants for efficiency and stability
-
and models open new paradigms for analyzing ocean remote sensing data. However, unlike regular images where correlations are typically local—favoring the use of standard convolutional neural networks
-
particular neural networks. A list of members of the statistics group can be found here. The statistics group is embedded within a larger data science initiative at the University of Twente’s department
-
., Denil, M., Gomez, S., Hoffman, M. W., Pfau, D., Schaul, T., … & De Freitas, (2016). Learning to learn by gradient descent by gradient descent. Advances in neural information processing systems, 29
-
cooperation with Kopter Germany GmbH and the Engineering Risk Analysis Group of Prof. Straub, which provides information on both the health and the actual stress of helicopter components. For this so-called
-
architectures which leverage our increasing understanding of the behaviour of neural networks trained with DP to ameliorate these trade-offs in biomedical applications. - Foundations of private machine learning