22 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Osnabrück UniversityDE3 papers
- Commonwealth Scientific and Industrial Research OrganisationAU2 papers
- German Research Centre for Artificial IntelligenceDE2 papers
- Hochschule OsnabrückDE2 papers
- Max Planck Institute for Radio AstronomyDE2 papers
- Aalto UniversityFI1 paper
- AgroParisTechFR1 paper
- AgroscopeCH1 paper
- Astronomy and SpaceAU1 paper
- Australia Telescope National FacilityAU1 paper
- Bielefeld UniversityDE1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
8 papers
Kriging prior Regression: A Case for Kriging-Based Spatial Features with TabPFN in Soil Mapping
Jonas Schmidinger, Viacheslav Barkov, Sebastian Vogel +2
Machine learning and geostatistics are two fundamentally different frameworks for predicting and spatially mapping soil properties. Geostatistics leverages the spatial structure of…
Modern Neural Networks for Small Tabular Datasets: The New Default for Field-Scale Digital Soil Mapping?
Viacheslav Barkov, Jonas Schmidinger, Robin Gebbers +1
In the field of pedometrics, tabular machine learning is the predominant method for soil property prediction from remote and proximal soil sensing data, forming a central component…
Evaluate with the Inverse: Efficient Approximation of Latent Explanation Quality Distribution
Carlos Eiras-Franco, Anna Hedström, Marina M. -C. Höhne
Obtaining high-quality explanations of a model's output enables developers to identify and correct biases, align the system's behavior with human values, and ensure ethical complia…
LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping
J. Schmidinger, S. Vogel, V. Barkov +33
Digital soil mapping (DSM) relies on a broad pool of statistical methods, yet determining the optimal method for a given context remains challenging and contentious. Benchmarking s…
An Efficient Model-Agnostic Approach for Uncertainty Estimation in Data-Restricted Pedometric Applications
Viacheslav Barkov, Jonas Schmidinger, Robin Gebbers +1
This paper introduces a model-agnostic approach designed to enhance uncertainty estimation in the predictive modeling of soil properties, a crucial factor for advancing pedometrics…
Exploring the time variability of the Solar Wind using LOFAR pulsar data
S. C. Susarla, A. Chalumeau, C. Tiburzi +22
High-precision pulsar timing is highly dependent on precise and accurate modeling of any effects that impact the data. It was shown that commonly used Solar Wind models do not accu…
RadioAstron Space VLBI Imaging of the jet in M87: I. Detection of high brightness temperature at 22 GHz
Jae-Young Kim, Tuomas Savolainen, Petr Voitsik +19
We present results from the first 22 GHz space very-long-baseline interferometric (VLBI) imaging observations of M87 by RadioAstron. As a part of the Nearby AGN Key Science Program…
A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements
Silvia Makowski, Lena Jäger, Ahmed Abdelwahab +2
We study the problem of inferring readers' identities and estimating their level of text comprehension from observations of their eye movements during reading. We develop a generat…