Jörg Martin

According to our database, Jörg Martin authored at least 12 papers between 2020 and 2026.

Collaborative distances:

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

2026

cc-Shapley: Measuring Multivariate Feature Importance Needs Causal Context.

Jörg Martin, Stefan Haufe

CoRR, February, 2026

2025

Deep Errors-in-Variables using a diffusion model.

Josua Faller, Jörg Martin, Clemens Elster

Mach. Learn., April, 2025

Optimal Subspace Inference for the Laplace Approximation of Bayesian Neural Networks.

Josua Faller, Jörg Martin

CoRR, February, 2025

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