Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks. - Jörg Wagner; Jan Mathias Köhler; Tobias Gindele; Leon Hetzel; Jakob Thaddäus Wiedemer; Sven Behnke (CVPR, 2019)

Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution. - Leon Hetzel; Simon Böhm; Niki Kilbertus; Stephan Günnemann; Mohammad Lotfollahi; Fabian J. Theis (NeurIPS, 2022)

Predicting single-cell perturbation responses for unseen drugs. - Leon Hetzel; Simon Böhm; Niki Kilbertus; Stephan Günnemann; Mohammad Lotfollahi; Fabian J. Theis (CoRR, 2022)

Uncertainty Quantification for Atlas-Level Cell Type Transfer. - Jan P. Engelmann; Leon Hetzel; Giovanni Palla; Lisa Sikkema; Malte Lücken; Fabian J. Theis (CoRR, 2022)

MAGNet: Motif-Agnostic Generation of Molecules from Shapes. - Leon Hetzel; Johanna Sommer; Bastian Rieck; Fabian J. Theis; Stephan Günnemann (CoRR, 2023)

The power of motifs as inductive bias for learning molecular distributions. - Johanna Sommer; Leon Hetzel; David Lüdke; Fabian J. Theis; Stephan Günnemann (CoRR, 2023)

Expressivity and Generalization: Fragment-Biases for Molecular GNNs. - Tom Wollschläger; Niklas Kemper; Leon Hetzel; Johanna Sommer; Stephan Günnemann (ICML, 2024)

Unified Guidance for Geometry-Conditioned Molecular Generation. - Sirine Ayadi; Leon Hetzel; Johanna Sommer; Fabian J. Theis; Stephan Günnemann (NeurIPS, 2024)

MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds. - Leon Hetzel; Johanna Sommer; Bastian Rieck; Fabian J. Theis; Stephan Günnemann (ICLR, 2025)

Targeted AMP generation through controlled diffusion with efficient embeddings. - Diogo Soares; Leon Hetzel; Paulina Szymczak; Fabian J. Theis; Stephan Günnemann; Ewa Szczurek (CoRR, 2025)

Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation. - Alessandro Palma; Sergei Rybakov; Leon Hetzel; Stephan Günnemann; Fabian J. Theis (CoRR, 2025)