Catastrophic Forgetting: Still a Problem for DNNs. - Benedikt Pfülb; Alexander Gepperth; Saad Abdullah; André Kilian (ICANN (1), 2018)

Flow-based Throughput Prediction using Deep Learning and Real-World Network Traffic. - Christoph Hardegen; Benedikt Pfülb; Sebastian Rieger; Alexander Gepperth; Sven Reißmann (CNSM, 2019)

A Study of Deep Learning for Network Traffic Data Forecasting. - Benedikt Pfülb; Christoph Hardegen; Alexander Gepperth; Sebastian Rieger (ICANN (4), 2019)

A comprehensive, application-oriented study of catastrophic forgetting in DNNs. - Benedikt Pfülb; Alexander Gepperth (ICLR (Poster), 2019)

Gradient-based training of Gaussian Mixture Models in High-Dimensional Spaces. - Alexander Gepperth; Benedikt Pfülb (CoRR, 2019)

A Rigorous Link Between Self-Organizing Maps and Gaussian Mixture Models. - Alexander Gepperth; Benedikt Pfülb (ICANN (2), 2020)

Predicting Network Flow Characteristics Using Deep Learning and Real-World Network Traffic. - Christoph Hardegen; Benedikt Pfülb; Sebastian Rieger; Alexander Gepperth (IEEE Trans. Netw. Serv. Manag., 2020)

Image Modeling with Deep Convolutional Gaussian Mixture Models. - Alexander Gepperth; Benedikt Pfülb (IJCNN, 2021)

Overcoming Catastrophic Forgetting with Gaussian Mixture Replay. - Benedikt Pfülb; Alexander Gepperth (IJCNN, 2021)

The Boolean Dilemma: Representing Gender as Data Type. - Natalie Kiesler; Benedikt Pfülb (Koli Calling, 2021)

Continual Learning with Fully Probabilistic Models. - Benedikt Pfülb; Alexander Gepperth; Benedikt Bagus (CoRR, 2021)

Gradient-Based Training of Gaussian Mixture Models for High-Dimensional Streaming Data. - Alexander Gepperth; Benedikt Pfülb (Neural Process. Lett., 2021)

Continual Learning with Deep Learning Methods in an Application-Oriented Context. - Benedikt Pfülb (CoRR, 2022)

Continual Learning with Deep Learning Methods in an Application-Oriented Context. - Benedikt Pfülb (Hochschule Fulda, 2022)

Higher Education Programming Competencies: A Novel Dataset. - Natalie Kiesler; Benedikt Pfülb (ICANN (8), 2023)