Marius Köppel

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 15

Top Topics

Invariant Representation

Top Venues

Publications

Tim Klausmann, Marius Köppel, Daniel Schunk, Isabell Zipperle
Can machine learning solve the challenge of adaptive learning and the individualization of learning paths? A field experiment in an online learning platform. CoRR (2024)
Mattia Cerrato, Marius Köppel, Philipp Wolf, Stefan Kramer
10 Years of Fair Representations: Challenges and Opportunities. CoRR (2024)
Marius Köppel, Jan-Philipp Muttach, Gerrit Hornung
Google Topics as a way out of the cookie dilemma? CoRR (2024)
Jan-Philipp Muttach, Marius Köppel, Gerrit Hornung
Google Topics als Ausweg aus dem Cookie-Dilemma? - Rechtliche Anforderungen an die technische Alternative zur individualisierten Werbung im Internet. Comput. und Recht 39 (10) (2023)
Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer
Invariant Representations with Stochastically Quantized Neural Networks. AAAI (2023)
Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel
The Case for Correctability in Fair Machine Learning. EWAF (2023)
Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer
Fair Group-Shared Representations with Normalizing Flows. CoRR (2022)
Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel, Alexander Segner, Roberto Esposito, Stefan Kramer
Fair Interpretable Representation Learning with Correction Vectors. CoRR (2022)
Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer
Invariant Representations with Stochastically Quantized Neural Networks. CoRR (2022)
Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer
Fair Interpretable Learning via Correction Vectors. CoRR (2022)
Julia Siekiera, Marius Köppel, Edwin Simpson, Kevin Stowe, Iryna Gurevych, Stefan Kramer
Ranking Creative Language Characteristics in Small Data Scenarios. ICCC (2022)
Julia Siekiera, Marius Köppel, Edwin Simpson, Kevin Stowe, Iryna Gurevych, Stefan Kramer
Ranking Creative Language Characteristics in Small Data Scenarios. CoRR (2020)
Mattia Cerrato, Marius Köppel, Alexander Segner, Roberto Esposito, Stefan Kramer
Fair pairwise learning to rank. DSAA (2020)
Marius Köppel, Alexander Segner, Martin Wagener, Lukas Pensel, Andreas Karwath, Stefan Kramer
Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance. ECML/PKDD (3) (2019)
Marius Köppel, Alexander Segner, Martin Wagener, Lukas Pensel, Andreas Karwath, Stefan Kramer
Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance. CoRR (2019)