Jonas Dippel

22 papers A* 4Journal 16Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Atlas 2 - Foundation models for clinical deployment.
CoRR
Maximilian Alber, Timo Milbich, Alexandra Carpen-Amarie, Stephan Tietz, Jonas Dippel, Lukas Muttenthaler, Beatriz Perez Cancer, Alessandro Benetti, Panos Korfiatis, Elias Eulig, Jérôme Lüscher, Jiasen Wu, Sayed Abid Hashimi, Gabriel Dernbach, Simon Schallenberg, Neelay Shah, Moritz Krügener, Aniruddh Jammoria, Jake Matras, Patrick Duffy, Matt Redlon, Philipp Jurmeister, David Horst, Lukas Ruff, Klaus-Robert Müller, Frederick Klauschen, Andrew P. Norgan
2026 J jnl
Beyond Attention Heatmaps: How to Get Better Explanations for Multiple Instance Learning Models in Histopathology.
CoRR
Mina Jamshidi Idaji, Julius Hense, Tom Neuhäuser, Augustin Krause, Yanqing Luo, Oliver Eberle, Thomas Schnake, Laure Ciernik, Farnoush Rezaei Jafari, Reza Vahidimajd, Jonas Dippel, Christoph Walz, Frederick Klauschen, Andreas Mock, Klaus-Robert Müller
2025 J jnl
Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charité, and Aignostics.
CoRR
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, Kai Standvoss, Gabriel Dernbach, Edwin D. de Jong, Simon Schallenberg, Andreas Kunft, Helmut Hoffer von Ankershoffen, Gavin Schaeferle, Patrick Duffy, Matt Redlon, Philipp Jurmeister, David Horst, Lukas Ruff, Klaus-Robert Müller, Frederick Klauschen, Andrew P. Norgan
2025 J jnl
Explainable AI reveals Clever Hans effects in unsupervised learning models.
Nat. Mac. Intell.
Jacob R. Kauffmann, Jonas Dippel, Lukas Ruff, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon
2025 — conf
MeDi: Metadata-Guided Diffusion Models for Mitigating Biases in Tumor Classification.
MICCAI (14)
David Jacob Drexlin, Jonas Dippel, Julius Hense, Niklas Prenißl, Grégoire Montavon, Frederick Klauschen, Klaus-Robert Müller
2025 J jnl
MeDi: Metadata-Guided Diffusion Models for Mitigating Biases in Tumor Classification.
CoRR
David Jacob Drexlin, Jonas Dippel, Julius Hense, Niklas Prenißl, Grégoire Montavon, Frederick Klauschen, Klaus-Robert Müller
2025 A* conf
Objective drives the consistency of representational similarity across datasets.
ICML
Laure Ciernik, Lorenz Linhardt, Marco Morik, Jonas Dippel, Simon Kornblith, Lukas Muttenthaler
2025 J jnl
Towards Robust Foundation Models for Digital Pathology.
CoRR
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
2024 J jnl
AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics.
CoRR
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, Frederick Klauschen
2024 J jnl
Do Histopathological Foundation Models Eliminate Batch Effects? A Comparative Study.
CoRR
Jonah Kömen, Hannah Marienwald, Jonas Dippel, Julius Hense
2024 J jnl
RudolfV: A Foundation Model by Pathologists for Pathologists.
CoRR
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, Maximilian Alber
2024 J jnl
The Clever Hans Effect in Unsupervised Learning.
CoRR
Jacob R. Kauffmann, Jonas Dippel, Lukas Ruff, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon
2024 J jnl
Training objective drives the consistency of representational similarity across datasets.
CoRR
Laure Ciernik, Lorenz Linhardt, Marco Morik, Jonas Dippel, Simon Kornblith, Lukas Muttenthaler
2024 A* conf
xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology.
NeurIPS
Julius Hense, Mina Jamshidi Idaji, Oliver Eberle, Thomas Schnake, Jonas Dippel, Laure Ciernik, Oliver Buchstab, Andreas Mock, Frederick Klauschen, Klaus-Robert Müller
2024 J jnl
xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology.
CoRR
Julius Hense, Mina Jamshidi Idaji, Oliver Eberle, Thomas Schnake, Jonas Dippel, Laure Ciernik, Oliver Buchstab, Andreas Mock, Frederick Klauschen, Klaus-Robert Müller
2023 A* conf
Human alignment of neural network representations.
ICLR
Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith
2023 A* conf
Improving neural network representations using human similarity judgments.
NeurIPS
Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine L. Hermann, Andrew K. Lampinen, Simon Kornblith
2023 J jnl
Improving neural network representations using human similarity judgments.
CoRR
Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine L. Hermann, Andrew K. Lampinen, Simon Kornblith
2022 J jnl
Human alignment of neural network representations.
CoRR
Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith
2022 J jnl
Transfer Learning for Segmentation Problems: Choose the Right Encoder and Skip the Decoder.
CoRR
Jonas Dippel, Matthias Lenga, Thomas Goerttler, Klaus Obermayer, Johannes Höhne
2021 J jnl
Towards Fine-grained Visual Representations by Combining Contrastive Learning with Image Reconstruction and Attention-weighted Pooling.
CoRR
Jonas Dippel, Steffen Vogler, Johannes Höhne
2019 — conf
Automated Data Retrieval from Large-Scale Distributed Satellite Systems.
CASE
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, Christian Schurig, Sándor P. Fekete