Jörg Martin

According to our database, Jörg Martin authored at least 9 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of six.
• Erdős number of five.

2024

Finding the input features that reduce the entropy of a neural network's prediction.

Narbota Amanova, Jörg Martin, Clemens Elster

Appl. Intell., 2024

2023

About the generalizability of deep learning based image quality assessment in mammography.

Josua Faller, Narbota Amanova, Ruben E. van Engen, Jörg Martin, Clemens Elster

Mach. Learn. Sci. Technol., December, 2023

A framework for benchmarking uncertainty in deep regression.

Franko Schmähling, Jörg Martin, Clemens Elster

Appl. Intell., April, 2023

Aleatoric Uncertainty for Errors-in-Variables Models in Deep Regression.

Jörg Martin, Clemens Elster

Neural Process. Lett., 2023

2022

Explainability for deep learning in mammography image quality assessment.

Narbota Amanova, Jörg Martin, Clemens Elster

Mach. Learn. Sci. Technol., 2022

2021

Errors-in-Variables for deep learning: rethinking aleatoric uncertainty.

Jörg Martin, Clemens Elster

CoRR, 2021

About the regularity of the discriminator in conditional WGANs.

Jörg Martin

CoRR, 2021

Detecting unusual input to neural networks.

Jörg Martin, Clemens Elster

Appl. Intell., 2021

2020

Inspecting adversarial examples using the fisher information.

Jörg Martin, Clemens Elster

Neurocomputing, 2020