Perfect Match: A Simple Method for Learning Representations For Counterfactual Inference With Neural Networks. - Patrick Schwab; Lorenz Linhardt; Walter Karlen (CoRR, 2018)

TreePOD: Sensitivity-Aware Selection of Pareto-Optimal Decision Trees. - Thomas Mühlbacher; Lorenz Linhardt; Torsten Möller; Harald Piringer (IEEE Trans. Vis. Comput. Graph., 2018)

Learning Counterfactual Representations for Estimating Individual Dose-Response Curves. - Patrick Schwab; Lorenz Linhardt; Stefan Bauer; Joachim M. Buhmann; Walter Karlen (AAAI, 2020)

Drift Forensics of Malware Classifiers. - Theo Chow; Zeliang Kan; Lorenz Linhardt; Lorenzo Cavallaro; Daniel Arp; Fabio Pierazzi (AISec@CCS, 2023)

Human alignment of neural network representations. - Lukas Muttenthaler; Jonas Dippel; Lorenz Linhardt; Robert A. Vandermeulen; Simon Kornblith (ICLR, 2023)

Improving neural network representations using human similarity judgments. - Lukas Muttenthaler; Lorenz Linhardt; Jonas Dippel; Robert A. Vandermeulen; Katherine L. Hermann; Andrew K. Lampinen; Simon Kornblith (NeurIPS, 2023)

An Analysis of Human Alignment of Latent Diffusion Models. - Lorenz Linhardt; Marco Morik; Sidney Bender; Naima Elosegui Borras (CoRR, 2024)

Training objective drives the consistency of representational similarity across datasets. - Laure Ciernik; Lorenz Linhardt; Marco Morik; Jonas Dippel; Simon Kornblith; Lukas Muttenthaler (CoRR, 2024)

Preemptively pruning Clever-Hans strategies in deep neural networks. - Lorenz Linhardt; Klaus-Robert Müller; Grégoire Montavon (Inf. Fusion, 2024)

Connecting Concept Convexity and Human-Machine Alignment in Deep Neural Networks. - Teresa Dorszewski; Lenka Tetková; Lorenz Linhardt; Lars Kai Hansen (NLDL, 2025)

Latent Diffusion U-Net Representations Contain Positional Embeddings and Anomalies. - Jonas Loos; Lorenz Linhardt (CoRR, 2025)

Cat, Rat, Meow: On the Alignment of Language Model and Human Term-Similarity Judgments. - Lorenz Linhardt; Tom Neuhäuser; Lenka Tetková; Oliver Eberle (CoRR, 2025)

Code is law: how COMPAS affects the way the judiciary handles the risk of recidivism. - Christoph Engel; Lorenz Linhardt; Marcel Schubert (Artif. Intell. Law, 2025)

Breaking Out from the TESSERACT: Reassessing ML-based Malware Detection under Spatio-Temporal Drift. - Theo Chow; Mario D'Onghia; Lorenz Linhardt; Zeliang Kan; Daniel Arp; Lorenzo Cavallaro; Fabio Pierazzi (CoRR, 2025)