Viewport Forecasting in 360° Virtual Reality Videos with Machine Learning. - Johanna Vielhaben; Hüseyin Camalan; Wojciech Samek; Markus Wenzel 002 (AIVR, 2019)

USMPep: universal sequence models for major histocompatibility complex binding affinity prediction. - Johanna Vielhaben; Markus Wenzel 002; Wojciech Samek; Nils Strodthoff (BMC Bioinform., 2020)

Generative Neural Samplers for the Quantum Heisenberg Chain. - Johanna Vielhaben; Nils Strodthoff (CoRR, 2020)

Predicting the Binding of SARS-CoV-2 Peptides to the Major Histocompatibility Complex with Recurrent Neural Networks. - Johanna Vielhaben; Markus Wenzel 002; Eva Weicken; Nils Strodthoff (CoRR, 2021)

PredDiff: Explanations and interactions from conditional expectations. - Stefan Blücher; Johanna Vielhaben; Nils Strodthoff (Artif. Intell., 2022)

Sparse Subspace Clustering for Concept Discovery (SSCCD). - Johanna Vielhaben; Stefan Blücher; Nils Strodthoff (CoRR, 2022)

XAI-based Comparison of Audio Event Classifiers with different Input Representations. - Annika Frommholz; Fabian Seipel; Sebastian Lapuschkin; Wojciech Samek; Johanna Vielhaben (CBMI, 2023)

XAI-based Comparison of Input Representations for Audio Event Classification. - Annika Frommholz; Fabian Seipel; Sebastian Lapuschkin; Wojciech Samek; Johanna Vielhaben (CoRR, 2023)

Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees. - Johanna Vielhaben; Stefan Bluecher; Nils Strodthoff (Trans. Mach. Learn. Res., 2023)

PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits. - Maximilian Dreyer; Erblina Purelku; Johanna Vielhaben; Wojciech Samek; Sebastian Lapuschkin (XAI4CV, 2024)

Beyond Scalars: Concept-Based Alignment Analysis in Vision Transformers. - Johanna Vielhaben; Dilyara Bareeva; Jim Berend; Wojciech Samek; Nils Strodthoff (CoRR, 2024)

AudioMNIST: Exploring Explainable Artificial Intelligence for audio analysis on a simple benchmark. - Sören Becker 001; Johanna Vielhaben; Marcel Ackermann 001; Klaus-Robert Müller; Sebastian Lapuschkin; Wojciech Samek (J. Frankl. Inst., 2024)

Explainable AI for time series via Virtual Inspection Layers. - Johanna Vielhaben; Sebastian Lapuschkin; Grégoire Montavon; Wojciech Samek (Pattern Recognit., 2024)

Decoupling Pixel Flipping and Occlusion Strategy for Consistent XAI Benchmarks. - Stefan Bluecher; Johanna Vielhaben; Nils Strodthoff (Trans. Mach. Learn. Res., 2024)

Mechanistic understanding and validation of large AI models with SemanticLens. - Maximilian Dreyer; Jim Berend; Tobias Labarta; Johanna Vielhaben; Thomas Wiegand 001; Sebastian Lapuschkin; Wojciech Samek (CoRR, 2025)

FeatInv: Spatially resolved mapping from feature space to input space using conditional diffusion models. - Nils Neukirch; Johanna Vielhaben; Nils Strodthoff (CoRR, 2025)