6 citations · 12 across the 10 of their papers we have counts for
4 papers · 1 filter
Grounding Functional Similarity by Invariance-Aware Model Stitching
Ioannis Athanasiadis, Anmar Karmush, Michael Felsberg
In deep learning, functional similarity evaluation quantifies the extent to which independently trained models learn similar input--output relationships. In model stitching, functi…
Interactive Double Deep Q-network: Integrating Human Interventions and Evaluative Predictions in Reinforcement Learning of Autonomous Driving
Alkis Sygkounas, Ioannis Athanasiadis, Andreas Persson +2
Integrating human expertise with machine learning is crucial for applications demanding high accuracy and safety, such as autonomous driving. This study introduces Interactive Doub…
Prior Learning in Introspective VAEs
Ioannis Athanasiadis, Fredrik Lindsten, Michael Felsberg
Variational Autoencoders (VAEs) are a popular framework for unsupervised learning and data generation. A plethora of methods have been proposed focusing on improving VAEs, with the…
Certainty In, Certainty Out: REVQCs for Quantum Machine Learning
Hannah Helgesen, Michael Felsberg, Jan-Åke Larsson
The field of Quantum Machine Learning (QML) has emerged recently in the hopes of finding new machine learning protocols or exponential speedups for classical ones. Apart from probl…