Automated Data Retrieval from Large-Scale Distributed Satellite Systems. - Dominik Krupke; Volker Schaus; Andreas Haas; Michael Perk; Jonas Dippel; Benjamin Grzesik; Mohamed Khalil Ben Larbi; Enrico Stoll; Tom Haylock; Harald Konstanski; Kattia Flores Pozo; Mirue Choi; et al. (CASE, 2019)

Towards Fine-grained Visual Representations by Combining Contrastive Learning with Image Reconstruction and Attention-weighted Pooling. - Jonas Dippel; Steffen Vogler; Johannes Höhne (CoRR, 2021)

Transfer Learning for Segmentation Problems: Choose the Right Encoder and Skip the Decoder. - Jonas Dippel; Matthias Lenga; Thomas Goerttler; Klaus Obermayer; Johannes Höhne (CoRR, 2022)

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)

xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology. - Julius Hense; Mina Jamshidi Idaji; Oliver Eberle; Thomas Schnake; Jonas Dippel; Laure Ciernik; Oliver Buchstab; Andreas Mock; Frederick Klauschen; Klaus-Robert Müller (NeurIPS, 2024)

RudolfV: A Foundation Model by Pathologists for Pathologists. - Jonas Dippel; Barbara Feulner; Tobias Winterhoff; Simon Schallenberg; Gabriel Dernbach; Andreas Kunft; Stephan Tietz; Philipp Jurmeister; David Horst; Lukas Ruff; Klaus-Robert Müller; Frederick Klauschen; et al. (CoRR, 2024)

AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics. - Jonas Dippel; Niklas Prenißl; Julius Hense; Philipp Liznerski; Tobias Winterhoff; Simon Schallenberg; Marius Kloft; Oliver Buchstab; David Horst; Maximilian Alber; Lukas Ruff; Klaus-Robert Müller; et al. (CoRR, 2024)

The Clever Hans Effect in Unsupervised Learning. - Jacob R. Kauffmann; Jonas Dippel; Lukas Ruff; Wojciech Samek; Klaus-Robert Müller; Grégoire Montavon (CoRR, 2024)

Do Histopathological Foundation Models Eliminate Batch Effects? A Comparative Study. - Jonah Kömen; Hannah Marienwald; Jonas Dippel; Julius Hense (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)

Explainable AI Reveals Clever Hans Effects in Unsupervised Learning Models: Code. - Jacob R. Kauffmann; Jonas Dippel; Lukas Ruff; Wojciech Samek; Klaus-Robert Müller; Grégoire Montavon (Zenodo, 2024)

Explainable AI reveals Clever Hans effects in unsupervised learning models. - Jacob R. Kauffmann; Jonas Dippel; Lukas Ruff; Wojciech Samek; Klaus-Robert Müller; Grégoire Montavon (Nat. Mac. Intell., 2025)

Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charité, and Aignostics. - Maximilian Alber; Stephan Tietz; Jonas Dippel; Timo Milbich; Timothée Lesort; Panos Korfiatis; Moritz Krügener; Beatriz Perez Cancer; Neelay Shah; Alexander Möllers; Philipp Seegerer; Alexandra Carpen-Amarie; et al. (CoRR, 2025)

MeDi: Metadata-Guided Diffusion Models for Mitigating Biases in Tumor Classification. - David Jacob Drexlin; Jonas Dippel; Julius Hense; Niklas Prenißl; Grégoire Montavon; Frederick Klauschen; Klaus-Robert Müller (CoRR, 2025)

Towards Robust Foundation Models for Digital Pathology. - Jonah Kömen; Edwin D. de Jong; Julius Hense; Hannah Marienwald; Jonas Dippel; Philip Naumann; Eric Marcus; Lukas Ruff; Maximilian Alber; Jonas Teuwen; Frederick Klauschen; Klaus-Robert Müller (CoRR, 2025)