76 citations · 126 across the 14 of their papers we have counts for
5 papers · 1 filter
Argument Mining Driven Analysis of Peer-Reviews
Michael Fromm, Evgeniy Faerman, Max Berrendorf +7
Peer reviewing is a central process in modern research and essential for ensuring high quality and reliability of published work. At the same time, it is a time-consuming process a…
Diversity Aware Relevance Learning for Argument Search
Michael Fromm, Max Berrendorf, Sandra Obermeier +2
In this work, we focus on the problem of retrieving relevant arguments for a query claim covering diverse aspects. State-of-the-art methods rely on explicit mappings between claims…
Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels
Valentyn Melnychuk, Evgeniy Faerman, Ilja Manakov +1
Unlabeled data is often abundant in the clinic, making machine learning methods based on semi-supervised learning a good match for this setting. Despite this, they are currently re…
Learning Self-Expression Metrics for Scalable and Inductive Subspace Clustering
Julian Busch, Evgeniy Faerman, Matthias Schubert +1
Subspace clustering has established itself as a state-of-the-art approach to clustering high-dimensional data. In particular, methods relying on the self-expressiveness property ha…
PushNet: Efficient and Adaptive Neural Message Passing
Julian Busch, Jiaxing Pi, Thomas Seidl
Message passing neural networks have recently evolved into a state-of-the-art approach to representation learning on graphs. Existing methods perform synchronous message passing al…