Simulation Data Mining for Supporting Bridge Design. - Steven Burrows; Benno Stein 001; Jörg Frochte; David Wiesner; Katja Müller (AusDM, 2011)

Evaluation and Adaptation of Techniques for Higher Index DAE with Respect to Real-Time Simulation. - Jörg Frochte (Simul. Notes Eur., 2012)

Webis Simulation Data Mining Bridge Models Corpus 2012 (Webis-SDMbridge-12). - Steven Burrows; Benno Stein 001; Jörg Frochte; Tim Gollub; Peter Hirsch 003; Jens Opolka; Tom Paschke; Michael Völske (Zenodo, 2012)

Learning Overlap Optimization for Domain Decomposition Methods. - Steven Burrows; Jörg Frochte; Michael Völske; Ana Belén Martínez Torres; Benno Stein 001 (PAKDD (1), 2013)

Success Prediction System for Student Counseling using Data Mining. - Jörg Frochte; Irina Bernst (KDIR, 2016)

A Learning Approach for Ill-Posed Optimisation Problems. - Jörg Frochte; Stephen Marsland (AusDM, 2019)

Case Study on Model-based Application of Machine Learning using Small CAD Databases for Cost Estimation. - Stefan Börzel; Jörg Frochte (KDIR, 2019)

A Learning Approach for Optimizing Robot Behavior Selection Algorithm. - Basile Tousside; Janis Mohr; Marco Schmidt; Jörg Frochte (ICIRA, 2020)

Regression learning on patches. - Jörg Frochte; Stephen Marsland (SSCI, 2020)

Explainability and Continuous Learning with Capsule Networks. - Janis Mohr; Basile Tousside; Marco Schmidt; Jörg Frochte (KDIR, 2021)

An Approach to One-shot Identification with Neural Networks. - Janis Mohr; Finn Breidenbach; Jörg Frochte (IJCCI, 2021)

Group and Exclusive Sparse Regularization-based Continual Learning of CNNs. - Basile Tousside; Janis Mohr; Jörg Frochte (Canadian AI, 2022)

Towards Explainability in Modern Educational Data Mining: A Survey. - Basile Tousside; Yashwanth Dama; Jörg Frochte (KDIR, 2022)

Investigation of Capsule Networks Regarding their Potential of Explainability and Image Rankings. - Felizia Quetscher; Christof Kaufmann; Jörg Frochte (ICAART (3), 2022)

Towards Robust Continual Learning using an Enhanced Tree-CNN. - Basile Tousside; Lukas Friedrichsen; Jörg Frochte (ICAART (3), 2022)

Shared Tasks as Tutorials: A Methodical Approach. - Theresa Elstner; Frank Loebe; Yamen Ajjour; Christopher Akiki; Alexander Bondarenko 001; Maik Fröbe; Lukas Gienapp; Nikolay Kolyada; Janis Mohr; Stephan Sandfuchs; Matti Wiegmann; Jörg Frochte; et al. (AAAI, 2023)

Success Factors for Mathematical e-Learning Exercises Focusing First-Year Students. - Malte Neugebauer; Basile Tousside; Jörg Frochte (CSEDU (2), 2023)

Steigerung von Lernerfolg und Motivation durch gamifizierte Mathematik-Aufgaben in Lernmanagementsystemen. - Malte Neugebauer; Jörg Frochte (DELFI, 2023)

Multiple Additive Neural Networks: A Novel Approach to Continuous Learning in Regression and Classification. - Janis Mohr; Basile Tousside; Marco Schmidt; Jörg Frochte (IJCCI, 2023)

Efficient Learning Processes by Design: Analysis of Usage Patterns in Differently Designed Digital Self-Learning Environments. - Malte Neugebauer; Ralf Erlebach; Christof Kaufmann; Janis Mohr; Jörg Frochte (CSEDU (2), 2024)

Angewandte künstliche Intelligenz im Verbund verschiedener Fachbereiche. - Christian Bockermann; Jörg Frochte; Daniel Schilberg (INFORMATIK, 2024)

CNNs Sparsification and Expansion for Continual Learning. - Basile Tousside; Jörg Frochte; Tobias Meisen (ICAART (2), 2024)

Dynamic Capacity Expansion in Continual Learning: The eSECL Approach. - Basile Tousside; Jörg Frochte; Tobias Meisen (ICAART (Revised Selected Paper, 1), 2024)

Classification of Shared Tasks Used in Teaching. - Theresa Elstner; Bärbel Hanle; Frank Loebe; Maik Fröbe; Nikolay Kolyada; Janis Mohr; Jörg Frochte; Sven Hofmann; Benno Stein 001; Martin Potthast (ITiCSE (1), 2024)

Exploring Student Expectations and Confidence in Learning Analytics. - Hayk Asatryan; Basile Tousside; Janis Mohr; Malte Neugebauer; Hildo Bijl; Paul Spiegelberg; Claudia Frohn-Schauf; Jörg Frochte (LAK, 2024)