Sicco Verwer, Christian A. Hammerschmidt (2017), flexfringe: A Passive Automaton Learning Package, L. O'Conner (Eds.), In 2017 IEEE International Conference on Software Maintenance and Evolution, ICSME 2017 p.638-642, IEEE.

Christian Hammerschmidt, Samuel Marchal, Radu State, Sicco Verwer (2016), Behavioral Clustering of Non-Stationary IP Flow Record Data, In 12th International Conference on Network and Service Management CNSM 2016 p.253-257, IEEE.

Christian Hammerschmidt, Samuel Marchal, Radu State, Nino Pellegrino, Sicco Verwer (2016), Efficient Learning of Communication Profiles from IP Flow Records, Patrick Kellenberger (Eds.), In Proceedings - 2016 IEEE 41st Conference on Local Computer Networks, LCN 2016 p.1-4, IEEE.

Christian Hammerschmidt, Benjamin Loos, Radu State, Thomas Engel, Sicco Verwer (2016), Flexible State-Merging for learning (P)DFAs in Python, S. Verwer, M. van Zaanen, R. Smetsers (Eds.), In Proceedings of The 13th International Conference on Grammatical Inference Volume 57 p.154-159, JMLR.

Marcos L. P. Bueno, Arjen Hommersom, Peter J. F. Lucas, Sicco Verwer, Alexis Linard (2016), Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: An Industrial Case, A. Antonucci, G. Corani, C.P. de Campos (Eds.), In Proceedings of the Eighth International Conference on Probabilistic Graphical Models Volume 52 p.50-61, JMLR.

Nino Pellegrino, Christian Hammerschmidt, Sicco Verwer, Qin Lin (2016), Learning Deterministic Finite Automata from Innite Alphabets, S. Verwer, M. van Zaanen, R. Smetsers (Eds.), In Proceedings of The 13th International Conference on Grammatical Inference Volume 57 p.69-72, JMLR.

Sicco Verwer, Menno van Zaanen, Rick Smetsers (Eds.) (2016), Proceedings of the 13th International Conference on Grammatical Inference ICGI: JMLR Workshop and Conference Proceedings , JMLR.

R Smetsers, M Volpato, FW Vaandrager, SE Verwer (2014), Bigger is not always better: on the quality of hypotheses in active automata learning, A Clark, M Kanazawa, R Yoshinaka (Eds.), In Proceedings of the 12th International Conference of Grammatical Inference p.167-181.

F Aarts, H Kuppens, J Tretmans, FW Vaandrager, SE Verwer (2014), Improving active Mealy machine learning for protocol conformance testing, In Machine Learning Volume 96 p.189-224.

A Labarre, SE Verwer (2014), Merging partially labelled trees: hardness and a declarative programming solution, In IEEE - ACM Transactions on Computational Biology and Bioinformatics Volume 11 p.389-397.