5 citations · 5 across the 2 of their papers we have counts for
5 papers
Fair Interpretable Representation Learning with Correction Vectors
Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel +3
Neural network architectures have been extensively employed in the fair representation learning setting, where the objective is to learn a new representation for a given vector whi…
Fair Interpretable Learning via Correction Vectors
Mattia Cerrato, Marius Köppel, Alexander Segner +1
Neural network architectures have been extensively employed in the fair representation learning setting, where the objective is to learn a new representation for a given vector whi…
The Mu3e Data Acquisition
Heiko Augustin, Niklaus Berger, Alessandro Bravar +25
The Mu3e experiment aims to find or exclude the lepton flavour violating decay with a sensitivity of one in 10 muon decays. The first phase of the experim…
Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance
Marius Köppel, Alexander Segner, Martin Wagener +3
We present a pairwise learning to rank approach based on a neural net, called DirectRanker, that generalizes the RankNet architecture. We show mathematically that our model is refl…
Performance of the large scale HV-CMOS pixel sensor MuPix8
H. Augustin, N. Berger, C. Blattgerste +26
The Mu3e experiment is searching for the charged lepton flavour violating decay , aiming for an ultimate sensitivity of one in decays. In an…