15 citations · 23 across the 8 of their papers we have counts for
8 papers
Scaling Experiments in Self-Supervised Cross-Table Representation Learning
Maximilian Schambach, Dominique Paul, Johannes S. Otterbach
To analyze the scaling potential of deep tabular representation learning models, we introduce a novel Transformer-based architecture specifically tailored to tabular data and cross…
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models
Julien Siems, Konstantin Ditschuneit, Winfried Ripken +4
Generalized Additive Models (GAMs) have recently experienced a resurgence in popularity due to their interpretability, which arises from expressing the target value as a sum of non…
Uncovering the Inner Workings of STEGO for Safe Unsupervised Semantic Segmentation
Alexander Koenig, Maximilian Schambach, Johannes Otterbach
Self-supervised pre-training strategies have recently shown impressive results for training general-purpose feature extraction backbones in computer vision. In combination with the…
Interpretable Reinforcement Learning via Neural Additive Models for Inventory Management
Julien Siems, Maximilian Schambach, Sebastian Schulze +1
The COVID-19 pandemic has highlighted the importance of supply chains and the role of digital management to react to dynamic changes in the environment. In this work, we focus on d…
Spectral Reconstruction and Disparity from Spatio-Spectrally Coded Light Fields via Multi-Task Deep Learning
Maximilian Schambach, Jiayang Shi, Michael Heizmann
We present a novel method to reconstruct a spectral central view and its aligned disparity map from spatio-spectrally coded light fields. Since we do not reconstruct an intermediat…
Microlens array grid estimation, light field decoding, and calibration
Maximilian Schambach, Fernando Puente León
We quantitatively investigate multiple algorithms for microlens array grid estimation for microlens array-based light field cameras. Explicitly taking into account natural and mech…
The Proca Field in Curved Spacetimes and its Zero Mass Limit
Maximilian Schambach, Ko Sanders
We investigate the classical and quantum Proca field (a massive vector potential) of mass in arbitrary globally hyperbolic spacetimes and in the presence of external sources.…
Quantization of the Proca field in curved spacetimes - A study of mass dependence and the zero mass limit
Maximilian Schambach
In this thesis we investigate the Proca field in arbitrary globally hyperbolic curved spacetimes. We rigorously construct solutions to the classical Proca equation, including exter…