Jonas Dippel

According to our database, Jonas Dippel authored at least 12 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, Kai Standvoss, Gabriel Dernbach, Edwin 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

CoRR, January, 2025

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

Do Histopathological Foundation Models Eliminate Batch Effects? A Comparative Study.

Jonah Kömen, Hannah Marienwald, Jonas Dippel, Julius Hense

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

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, Frederick Klauschen

CoRR, 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, Maximilian Alber

CoRR, 2024

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

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Human alignment of neural network representations.

Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

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

2021

Towards Fine-grained Visual Representations by Combining Contrastive Learning with Image Reconstruction and Attention-weighted Pooling.

Jonas Dippel, Steffen Vogler, Johannes Höhne

CoRR, 2021

2019

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, Christian Schurig, Sándor P. Fekete

Proceedings of the 15th IEEE International Conference on Automation Science and Engineering, 2019