Maximilian Alber

According to our database1, Maximilian Alber authored at least 17 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics.
CoRR, 2024

RudolfV: A Foundation Model by Pathologists for Pathologists.
CoRR, 2024

2023
Leveraging weak complementary labels to improve semantic segmentation of hepatocellular carcinoma and cholangiocarcinoma in H&E-stained slides.
CoRR, 2023

2020
Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images.
AI and ML for Digital Pathology, 2020

Balancing the composition of word embeddings across heterogenous data sets.
CoRR, 2020

2019
The (Un)reliability of Saliency Methods.
Proceedings of the Explainable AI: Interpreting, 2019

Software and Application Patterns for Explanation Methods.
Proceedings of the Explainable AI: Interpreting, 2019

Efficient learning machines: from kernel methods to deep learning.
PhD thesis, 2019

iNNvestigate Neural Networks!
J. Mach. Learn. Res., 2019

Software and application patterns for explanation methods.
CoRR, 2019

Explanations can be manipulated and geometry is to blame.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Backprop Evolution.
CoRR, 2018

Learning how to explain neural networks: PatternNet and PatternAttribution.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
The (Un)reliability of saliency methods.
CoRR, 2017

PatternNet and PatternLRP - Improving the interpretability of neural networks.
CoRR, 2017

An Empirical Study on The Properties of Random Bases for Kernel Methods.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Distributed Optimization of Multi-Class SVMs.
CoRR, 2016


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