5 citations · 10 across the 7 of their papers we have counts for
9 papers
Rethinking Structural Anomaly Detection: From Decision Boundaries to Projection Operators
Alexander Bauer
Most existing anomaly detection methods rely on estimating a probability density or learning an enclosing decision boundary, implicitly assuming that normal data occupies a region…
Noise & pattern: identity-anchored Tikhonov regularization for robust structural anomaly detection
Alexander Bauer, Klaus-Robert Müller
Anomaly detection plays a pivotal role in automated industrial inspection, aiming to identify subtle or rare defects in otherwise uniform visual patterns. As collecting representat…
Self-Supervised Training with Autoencoders for Visual Anomaly Detection
Alexander Bauer, Shinichi Nakajima, Klaus-Robert Müller
We focus on a specific use case in anomaly detection where the distribution of normal samples is supported by a lower-dimensional manifold. Here, regularized autoencoders provide a…
Registration for Incomplete Non-Gaussian Functional Data
Alexander Bauer, Fabian Scheipl, Helmut Küchenhoff +1
Accounting for phase variability is a critical challenge in functional data analysis. To separate it from amplitude variation, functional data are registered, i.e., their observed…
Polynomial-Time Exact MAP Inference on Discrete Models with Global Dependencies
Alexander Bauer, Shinichi Nakajima
Considering the worst-case scenario, junction tree algorithm remains the most general solution for exact MAP inference with polynomial run-time guarantees. Unfortunately, its main…
Towards Best Practice in Explaining Neural Network Decisions with LRP
Maximilian Kohlbrenner, Alexander Bauer, Shinichi Nakajima +3
Within the last decade, neural network based predictors have demonstrated impressive - and at times super-human - capabilities. This performance is often paid for with an intranspa…