Maximilian Alber

24 papers A* 1Journal 17Unranked 2

Year	Rank	Type	Title / 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`	Mind the Gap: Continuous Magnification Sampling for Pathology Foundation Models. CoRR Alexander Möllers, Julius Hense, Florian Schulz, Timo Milbich, Maximilian Alber, Lukas Ruff
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`	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`	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`	xCG: Explainable Cell Graphs for Survival Prediction in Non-Small Cell Lung Cancer. CoRR Marvin Sextro, Gabriel Dernbach, Kai Standvoss, Simon Schallenberg, Frederick Klauschen, Klaus-Robert Müller, Maximilian Alber, Lukas Ruff
2023	J	`jnl`	Leveraging weak complementary labels to improve semantic segmentation of hepatocellular carcinoma and cholangiocarcinoma in H&E-stained slides. CoRR Miriam Hägele, Johannes Eschrich, Lukas Ruff, Maximilian Alber, Simon Schallenberg, Adrien Guillot, Christoph Roderburg, Frank Tacke, Frederick Klauschen
2020	J	`jnl`	Balancing the composition of word embeddings across heterogenous data sets. CoRR Stephanie Brandl, David Lassner, Maximilian Alber
2020	—	`ch.`	Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images. AI and ML for Digital Pathology Philipp Seegerer, Alexander Binder, René Saitenmacher, Michael Bockmayr, Maximilian Alber, Philipp Jurmeister, Frederick Klauschen, Klaus-Robert Müller
2019	—	`—`	Efficient learning machines: from kernel methods to deep learning. Maximilian Alber
2019	A*	`conf`	Explanations can be manipulated and geometry is to blame. NeurIPS Ann-Kathrin Dombrowski, Maximilian Alber, Christopher J. Anders, Marcel Ackermann, Klaus-Robert Müller, Pan Kessel
2019	J	`jnl`	Explanations can be manipulated and geometry is to blame. CoRR Ann-Kathrin Dombrowski, Maximilian Alber, Christopher J. Anders, Marcel Ackermann, Klaus-Robert Müller, Pan Kessel
2019	—	`ch.`	Software and Application Patterns for Explanation Methods. Explainable AI Maximilian Alber
2019	J	`jnl`	Software and application patterns for explanation methods. CoRR Maximilian Alber
2019	—	`ch.`	The (Un)reliability of Saliency Methods. Explainable AI Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim
2019	J	`jnl`	iNNvestigate Neural Networks! J. Mach. Learn. Res. Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans
2018	J	`jnl`	Backprop Evolution. CoRR Maximilian Alber, Irwan Bello, Barret Zoph, Pieter-Jan Kindermans, Prajit Ramachandran, Quoc V. Le
2018	—	`conf`	Learning how to explain neural networks: PatternNet and PatternAttribution. ICLR (Poster) Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber, Klaus-Robert Müller, Dumitru Erhan, Been Kim, Sven Dähne
2018	J	`jnl`	iNNvestigate neural networks! CoRR Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans
2017	—	`conf`	An Empirical Study on The Properties of Random Bases for Kernel Methods. NIPS Maximilian Alber, Pieter-Jan Kindermans, Kristof Schütt, Klaus-Robert Müller, Fei Sha
2017	J	`jnl`	PatternNet and PatternLRP - Improving the interpretability of neural networks. CoRR Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber, Klaus-Robert Müller, Sven Dähne
2017	J	`jnl`	The (Un)reliability of saliency methods. CoRR Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim
2016	J	`jnl`	Distributed Optimization of Multi-Class SVMs. CoRR Maximilian Alber, Julian Zimmert, Ürün Dogan, Marius Kloft