Adaptive Dimensionality Adjustment for Online "Principal Component Analysis". - Nico Migenda; Ralf Möller 002; Wolfram Schenck (IDEAL (1), 2019)

Adaptive Dimensionality Reduction for Local Principal Component Analysis. - Nico Migenda; Wolfram Schenck (ETFA, 2020)

Towards Intelligent Legal Advisors for Document Retrieval and Question-Answering in German Legal Documents. - Christoph Hoppe; David Pelkmann; Nico Migenda; Daniel Hötte; Wolfram Schenck (AIKE, 2021)

Advanced Data Analytics Platform for Manufacturing Companies. - Tim Voigt; Nico Migenda; Marvin Schöne; David Pelkmann; Matthias Fricke; Wolfram Schenck; Martin Kohlhase (ETFA, 2021)

Variational Autoencoder based Novelty Detection for Real-World Time Series. - Luca Steinmann; Nico Migenda; Tim Voigt; Martin Kohlhase; Wolfram Schenck (MSIE, 2021)

Collaborative System for Question Answering in German Case Law Documents. - Christoph Hoppe; Nico Migenda; David Pelkmann; Daniel Hötte; Wolfram Schenck (PRO-VE, 2022)

Technical Readiness of Prescriptive Analytics Platforms: A Survey. - Marvin Niederhaus; Nico Migenda; Julian Weller; Wolfram Schenck; Martin Kohlhase (FRUCT, 2024)

NGPCA: Clustering of high-dimensional and non-stationary data streams. - Nico Migenda; Ralf Möller 002; Wolfram Schenck (Softw. Impacts, 2024)

Adaptive local Principal Component Analysis improves the clustering of high-dimensional data. - Nico Migenda; Ralf Möller 002; Wolfram Schenck (Pattern Recognit., 2024)