CODEC - Detecting Linear Correlations in Dense Clusters using coMAD-based PCA. - Maximilian Archimedes Xaver Hünemörder; Anna Beer 001; Daniyal Kazempour; Thomas Seidl 001 (LWDA, 2019)

SIDEKICK: Linear Correlation Clustering with Supervised Background Knowledge. - Maximilian Archimedes Xaver Hünemörder; Daniyal Kazempour; Peer Kröger; Thomas Seidl 001 (SISAP, 2019)

On coMADs and Principal Component Analysis. - Daniyal Kazempour; Max Hünemörder; Thomas Seidl 001 (SISAP, 2019)

Implicit Hough Transform Neural Networks for Subspace Clustering. - Julian Busch; Maximilian Hünemörder; Janis Held; Peer Kröger; Thomas Seidl 001 (ICDM (Workshops), 2021)

OAB - An Open Anomaly Benchmark Framework for Unsupervised and Semisupervised Anomaly Detection on Image and Tabular Data Sets. - Andreas Lohrer; Jan Deller; Maximilian Hünemörder; Peer Kröger (ICDM (Workshops), 2021)

AnyCORE - An Anytime Algorithm for Cluster Outlier REmoval. - Andreas Lohrer; Anna Beer 001; Maximilian Archimedes Xaver Hünemörder; Jenny Lauterbach; Thomas Seidl 001; Peer Kröger (LWDA, 2021)

Towards a Learned Index Structure for Approximate Nearest Neighbor Search Query Processing. - Maximilian Hünemörder; Peer Kröger; Matthias Renz (SISAP, 2021)

SePass: Semantic Password Guessing Using k-nn Similarity Search in Word Embeddings. - Maximilian Hünemörder; Levin Schäfer; Nadine Sarah Schüler; Michael Eichberg; Peer Kröger (ADMA (2), 2022)

Stirring the Pot - Teaching Reinforcement Learning Agents a "Push-Your-Luck" board game. - Maximilian Hünemörder; Mirjam Raffaela Bayer; Nadine Sarah Schüler; Peer Kröger (CoG, 2022)

A Simple and Explainable Method for Uncertainty Estimation using Attribute Prototype Networks. - Claudius Zelenka; Andrea Göhring; Daniyal Kazempour; Maximilian Hünemörder; Lars Schmarje; Peer Kröger (ICCV (Workshops), 2023)

Advances in Unsupervised Learning and Applications: Background knowledge driven subspace clustering, semantic password guessing and learned index structures. - Maximilian Archimedes Xaver Hünemörder (2023)

Over-optimistic evaluation and reporting of novel cluster algorithms: an illustrative study. - Theresa Ullmann; Anna Beer 001; Maximilian Hünemörder; Thomas Seidl 001; Anne-Laure Boulesteix (Adv. Data Anal. Classif., 2023)

An Exploratory Case Study on Data Breach Journalism. - Jukka Ruohonen; Kalle Hjerppe; Maximilian von Zastrow (ARES, 2024)

There is Strength in Numbers: A Comprehensive Study of Machine Learning Algorithms for Sex Identification on Animal Bone Remains. - Nadine Sarah Schüler; Ptolemaios D. Paxinos; Jing Yuan; Maximilian von Zastrow; Joris Peters; Peer Kröger (e-Science, 2024)

X Marks the Spot? Applying Recent Keypoint Detection Methods to Paleozoological Landmarking. - Nadine Sarah Schüler; Maximilian von Zastrow; Nadja Pöllath; Claudius Zelenka; Joris Peters (e-Science, 2024)

CoMadOut - a robust outlier detection algorithm based on CoMAD. - Andreas Lohrer; Daniyal Kazempour; Maximilian Hünemörder; Peer Kröger (Mach. Learn., 2024)