Jörg Martin - RankMe

15 papers Journal 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	cc-Shapley: Measuring Multivariate Feature Importance Needs Causal Context. CoRR Jörg Martin, Stefan Haufe
2025	J	`jnl`	Deep Errors-in-Variables using a diffusion model. Mach. Learn. Josua Faller, Jörg Martin, Clemens Elster
2025	J	`jnl`	Optimal Subspace Inference for the Laplace Approximation of Bayesian Neural Networks. CoRR Josua Faller, Jörg Martin
2024	J	`jnl`	Finding the input features that reduce the entropy of a neural network's prediction. Appl. Intell. Narbota Amanova, Jörg Martin, Clemens Elster
2023	J	`jnl`	A framework for benchmarking uncertainty in deep regression. Appl. Intell. Franko Schmähling, Jörg Martin, Clemens Elster
2023	J	`jnl`	About the generalizability of deep learning based image quality assessment in mammography. Mach. Learn. Sci. Technol. Josua Faller, Narbota Amanova, Ruben E. van Engen, Jörg Martin, Clemens Elster
2023	J	`jnl`	Aleatoric Uncertainty for Errors-in-Variables Models in Deep Regression. Neural Process. Lett. Jörg Martin, Clemens Elster
2022	J	`jnl`	Explainability for deep learning in mammography image quality assessment. Mach. Learn. Sci. Technol. Narbota Amanova, Jörg Martin, Clemens Elster
2021	J	`jnl`	A framework for benchmarking uncertainty in deep regression. CoRR Franko Schmähling, Jörg Martin, Clemens Elster
2021	J	`jnl`	About the regularity of the discriminator in conditional WGANs. CoRR Jörg Martin
2021	J	`jnl`	Detecting unusual input to neural networks. Appl. Intell. Jörg Martin, Clemens Elster
2021	J	`jnl`	Errors-in-Variables for deep learning: rethinking aleatoric uncertainty. CoRR Jörg Martin, Clemens Elster
2020	J	`jnl`	Detecting unusual input to neural networks. CoRR Jörg Martin, Clemens Elster
2020	J	`jnl`	Inspecting adversarial examples using the fisher information. Neurocomputing Jörg Martin, Clemens Elster
2019	J	`jnl`	Inspecting adversarial examples using the Fisher information. CoRR Jörg Martin, Clemens Elster