Benjamin Paaßen

According to our database, Benjamin Paaßen authored at least 53 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Diffusion-based Visual Counterfactual Explanations - Towards Systematic Quantitative Evaluation.

Philipp Väth, Alexander M. Frühwald, Benjamin Paaßen, Magda Gregorova

CoRR, 2023

Fairness in KI-Systemen.

Janine Strotherm, Alissa Müller, Barbara Hammer, Benjamin Paaßen

CoRR, 2023

Was wirkt? Eine Literaturstudie zur Wirksamkeit von Systemeigenschaften in Mathematik-Lernumgebungen.

Berit Blanc, Insa Reichow, Benjamin Paaßen

Proceedings of the DELFI 2023, 2023

2022

Reservoir Memory Machines as Neural Computers.

Benjamin Paaßen, Alexander Schulz, Terrence C. Stewart, Barbara Hammer

IEEE Trans. Neural Networks Learn. Syst., 2022

Recursive tree grammar autoencoders.

Benjamin Paaßen, Irena Koprinska, Kalina Yacef

Mach. Learn., 2022

Reservoir stack machines.

Benjamin Paaßen, Alexander Schulz, Barbara Hammer

Neurocomputing, 2022

Combining domain modelling and student modelling techniques in a single automated pipeline.

Gio Picones, Benjamin Paaßen, Irena Koprinska, Kalina Yacef

Proceedings of the 15th International Conference on Educational Data Mining, 2022

Faster Confidence Intervals for Item Response Theory via an Approximate Likelihood Profile.

Benjamin Paaßen, Christina Göpfert, Niels Pinkwart

Proceedings of the 15th International Conference on Educational Data Mining, 2022

Sparse Factor Autoencoders for Item Response Theory.

Benjamin Paaßen, Malwina Dywel, Melanie Fleckenstein, Niels Pinkwart

Proceedings of the 15th International Conference on Educational Data Mining, 2022

Few-shot Keypose Detection for Learning of Psychomotor Skills.

Benjamin Paaßen, Tobias Baumgartner, Mai Geisen, Nina Riedl, Milos Kravcik

Proceedings of the Second International Workshop on Multimodal Immersive Learning Systems (MILeS 2022) At the Seventeenth European Conference on Technology Enhanced Learning (EC-TEL 2022), 2022

Interpretable Knowledge Gain Prediction for Vocational Preparatory E-Learnings.

Benjamin Paaßen, Malwina Dywel, Melanie Fleckenstein, Niels Pinkwart

Proceedings of the Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners' and Doctoral Consortium, 2022

2021

Automatic Creativity Measurement in Scratch Programs Across Modalities.

Anastasia Kovalkov, Benjamin Paaßen, Avi Segal, Niels Pinkwart, Kobi Gal

IEEE Trans. Learn. Technol., 2021

An A*-algorithm for the Unordered Tree Edit Distance with Custom Costs.

Benjamin Paaßen

Proceedings of the Similarity Search and Applications - 14th International Conference, 2021

Graph Edit Networks.

Benjamin Paassen, Daniele Grattarola, Daniele Zambon, Cesare Alippi, Barbara Hammer

Proceedings of the 9th International Conference on Learning Representations, 2021

Deep learning for graphs.

Davide Bacciu, Filippo Maria Bianchi, Benjamin Paassen, Cesare Alippi

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

Next Steps for Next-step Hints: Lessons Learned from Teacher Evaluations of Automatic Programming Hints (Full Paper).

Benjamin Paaßen, Jessica McBroom, Bryn Jeffries, Irena Koprinska, Kalina Yacef

Proceedings of the Joint Proceedings of the Workshops at the International Conference on Educational Data Mining 2021 co-located with 14th International Conference on Educational Data Mining (EDM 2021), 2021

ast2vec: Utilizing Recursive Neural Encodings of Python Programs.

Benjamin Paaßen, Jessica McBroom, Bryn Jeffries, Irena Koprinska, Kalina Yacef

Proceedings of the 14th International Conference on Educational Data Mining, 2021

Analyzing Student Success and Mistakes in Virtual Microscope Structure Search Tasks.

Benjamin Paaßen, Andreas Bertsch, Katharina Langer-Fischer, Sylvio Rüdian, Xia Wang, Rupali Sinha, Jakub Kuzilek, Stefan Britsch, Niels Pinkwart

Proceedings of the 14th International Conference on Educational Data Mining, 2021

Modeling Creativity in Visual Programming: From Theory to Practice.

Anastasia Kovalkov, Benjamin Paassen, Avi Segal, Kobi Gal, Niels Pinkwart

Proceedings of the 14th International Conference on Educational Data Mining, 2021

Progress Networks as a Tool for Analysing Student Programming Difficulties.

Jessica McBroom, Benjamin Paassen, Bryn Jeffries, Irena Koprinska, Kalina Yacef

Proceedings of the ACE '21: 23rd Australasian Computing Education Conference, 2021

2020

The Gendered Nature and Malleability of Gamer Stereotypes.

Thekla Morgenroth, Michelle Stratemeyer, Benjamin Paaßen

Cyberpsychology Behav. Soc. Netw., 2020

Tree Echo State Autoencoders with Grammars.

Benjamin Paassen, Irena Koprinska, Kalina Yacef

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Reservoir memory machines.

Benjamin Paassen, Alexander Schulz

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019

Metric Learning for Structured Data.

Benjamin Paaßen

PhD thesis, 2019

A Comparison of the Quality of Data-Driven Programming Hint Generation Algorithms.

Thomas W. Price, Yihuan Dong, Rui Zhi, Benjamin Paaßen, Nicholas Lytle, Veronica Cateté, Tiffany Barnes

Int. J. Artif. Intell. Educ., 2019

Adversarial Edit Attacks for Tree Data.

Benjamin Paaßen

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019

Embeddings and Representation Learning for Structured Data.

Benjamin Paaßen, Claudio Gallicchio, Alessio Micheli, Alessandro Sperduti

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Dynamic fairness - Breaking vicious cycles in automatic decision making.

Benjamin Paaßen, Astrid Bunge, Carolin Hainke, Leon Sindelar, Matthias Vogelsang

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

2018

Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces.

Benjamin Paaßen, Christina Göpfert, Barbara Hammer

Neural Process. Lett., 2018

Expectation maximization transfer learning and its application for bionic hand prostheses.

Benjamin Paaßen, Alexander Schulz, Janne Hahne, Barbara Hammer

Neurocomputing, 2018

Tree Edit Distance Learning via Adaptive Symbol Embeddings: Supplementary Materials and Results.

Benjamin Paaßen

CoRR, 2018

Revisiting the tree edit distance and its backtracing: A tutorial.

Benjamin Paaßen

CoRR, 2018

Tree Edit Distance Learning via Adaptive Symbol Embeddings.

Benjamin Paaßen, Claudio Gallicchio, Alessio Micheli, Barbara Hammer

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

The Continuous Hint Factory - Providing Hints in Vast and Sparsely Populated Edit Distance Spaces.

Benjamin Paaßen, Barbara Hammer, Thomas William Price, Tiffany Barnes, Sebastian Gross, Niels Pinkwart

CoRR, 2017

Linear supervised transfer learning for the large margin nearest neighbor classifier.

Kolja Berger, Alexander Schulz, Benjamin Paaßen, Barbara Hammer

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

An EM transfer learning algorithm with applications in bionic hand prostheses.

Benjamin Paassen, Alexander Schulz, Janne Hahne, Barbara Hammer

Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Echo State Networks as Novel Approach for Low-Cost Myoelectric Control.

Cosima Prahm, Alexander Schulz, Benjamin Paaßen, Oskar Aszmann, Barbara Hammer, Georg Dorffner

Proceedings of the Artificial Intelligence in Medicine, 2017

2016

Adaptive structure metrics for automated feedback provision in intelligent tutoring systems.

Benjamin Paaßen, Bassam Mokbel, Barbara Hammer

Neurocomputing, 2016

Local Reject Option for Deterministic Multi-class SVM.

Johannes Kummert, Benjamin Paassen, Joris Jensen, Christina Göpfert, Barbara Hammer

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning.

Christina Göpfert, Benjamin Paassen, Barbara Hammer

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

Gaussian process prediction for time series of structured data.

Benjamin Paassen, Christina Göpfert, Barbara Hammer

Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Execution Traces as a Powerful Data Representation for Intelligent Tutoring Systems for Programming.

Benjamin Paaßen, Joris Jensen, Barbara Hammer

Proceedings of the 9th International Conference on Educational Data Mining, 2016

2015

Autonomous Learning of Representations.

Oliver Walter, Reinhold Haeb-Umbach, Bassam Mokbel, Benjamin Paaßen, Barbara Hammer

Künstliche Intell., 2015

Interview with Werner von Seelen.

Benjamin Paaßen

Künstliche Intell., 2015

Metric learning for sequences in relational LVQ.

Bassam Mokbel, Benjamin Paaßen, Frank-Michael Schleif, Barbara Hammer

Neurocomputing, 2015

Adaptive structure metrics for automated feedback provision in Java programming.

Benjamin Paassen, Bassam Mokbel, Barbara Hammer

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

A Toolbox for Adaptive Sequence Dissimilarity Measures for Intelligent Tutoring Systems.

Benjamin Paaßen, Bassam Mokbel, Barbara Hammer

Proceedings of the 8th International Conference on Educational Data Mining, 2015

2014

Learning interpretable kernelized prototype-based models.

Daniela Hofmann, Frank-Michael Schleif, Benjamin Paaßen, Barbara Hammer

Neurocomputing, 2014

Example-based feedback provision using structured solution spaces.

Sebastian Gross, Bassam Mokbel, Benjamin Paaßen, Barbara Hammer, Niels Pinkwart

Int. J. Learn. Technol., 2014

Efficient Adaptation of Structure Metrics in Prototype-Based Classification.

Bassam Mokbel, Benjamin Paaßen, Barbara Hammer

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

Adaptive distance measures for sequential data.

Bassam Mokbel, Benjamin Paaßen, Barbara Hammer

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Ontology-based Extraction of Structured Information from Publications on Preclinical Experiments for Spinal Cord Injury Treatments.

Benjamin Paassen, Andreas Stöckel, Raphael Dickfelder, Jan Philip Göpfert, Nicole Brazda, Tarek Kirchhoffer, Hans Werner Müller, Roman Klinger, Matthias Hartung, Philipp Cimiano

Proceedings of the Third Workshop on Semantic Web and Information Extraction, 2014

2013

Domain-Independent Proximity Measures in Intelligent Tutoring Systems.

Bassam Mokbel, Sebastian Gross, Benjamin Paaßen, Niels Pinkwart, Barbara Hammer

Proceedings of the 6th International Conference on Educational Data Mining, 2013