P. Altmeyer, G.J.A. Angela, A.J. Buszydlik, K.T. Dobiczek, A. van Deursen, C.C.S. Liem (2023), Endogenous Macrodynamics in Algorithic Recourse [VIDEO].

Patrick Altmeyer, Angela Giovan, Aleksander Buszydlik, Karol Dobiczek, Arie van Deursen, Cynthia C. S. Liem (2023), Endogenous Macrodynamics in Algorithmic Recourse, Cristina Ceballos (Eds.), In Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) p.418-431, IEEE .

P. Altmeyer, C.C.S. Liem, A. van Deursen (2023), Explaining Black-Box Models through Counterfactuals, In The Proceedings of the JuliaCon Conferences (JCON).

A.J. Bartlett, C.C.S. Liem, A. Panichella (2023), On the Strengths of Pure Evolutionary Algorithms in Generating Adversarial Examples, In The 16th International Workshop on Search-Based and Fuzz Testing, IEEE / ACM.

Cynthia C. S. Liem, Andrew M. Demetriou (2023), Treat societally impactful scientific insights as open-source software artifacts, L. O'Conner (Eds.), In Proceedings of the 2023 IEEE/ACM 45th International Conference on Software Engineering p.150-156, IEEE .

Ioannis Petros Samiotis, Christoph Lofi, Shaad Alaka, Cynthia C. S. Liem, Alessandro Bozzon (2022), Scriptoria: A Crowd-powered Music Transcription System, F. Laforest, R. Troncy, L. Médini, I. Herman (Eds.), In WWW 2022 - Companion Proceedings of the Web Conference 2022 p.256-259, Association for Computing Machinery (ACM).

Han-Yin Huang, Cynthia C.S. Liem (2022), Social Inclusion in Curated Contexts: Insights from Museum Practices, In Proceedings of 2022 5th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2022 p.300-309, Association for Computing Machinery (ACM).

Burak Yildiz, Hayley Hung, Jesse H. Krijthe, Cynthia C.S. Liem, Marco Loog, Gosia Migut, Frans A. Oliehoek, Annibale Panichella, Przemysław Pawełczak, Stjepan Picek, Mathijs de Weerdt, Jan van Gemert (2021), ReproducedPapers.org: Openly Teaching and Structuring Machine Learning Reproducibility, Bertrand Kerautret, Miguel Colom, Adrien Krähenbühl, Daniel Lopresti, Pascal Monasse, Hugues Talbot (Eds.), In Reproducible Research in Pattern Recognition - 3rd International Workshop, RRPR 2021, Revised Selected Papers p.3-11, Springer.

A. Panichella, C.C.S. Liem (2021), What Are We Really Testing in Mutation Testing for Machine Learning? A Critical Reflection, In 43rd International Conference on Software Engineering - New Ideas and Emerging Results p.66-70, ACM/IEEE.

C.C.S. Liem, C. Mostert (2020), Can't trust the feeling?: How open data reveals unexpected behavior of high-level music descriptors, In Proceedings of the 21st International Society for Music Information Retrieval Conference p.240-247.