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Gabriel Dax
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2020 – today
- 2024
- [b1]Gabriel Dax:
Aspects of Algorithmic Information Theory in Spatial Machine Learning. Technical University of Munich, Germany, 2024 - [c7]Florian Karl, Lukas Malte Kemeter, Gabriel Dax, Paulina Sierak:
Position: Embracing Negative Results in Machine Learning. ICML 2024 - [i2]Florian Karl, Lukas Malte Kemeter, Gabriel Dax, Paulina Sierak:
Position: Embracing Negative Results in Machine Learning. CoRR abs/2406.03980 (2024) - 2023
- [j1]Gabriel Dax
, Srilakshmi Nagarajan, Hao Li
Compression Supports Spatial Deep Learning. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 16: 702-713 (2023) - [c6]Andreas Koch
Machine Learning Application Benchmark. CF 2023: 229-235 - [c5]Hao Li
Semi-Supervised Learning from Street-View Images and OpenStreetMap for Automatic Building Height Estimation. GIScience 2023: 7:1-7:15 - [i1]Hao Li, Zhendong Yuan, Gabriel Dax, Gefei Kong, Hongchao Fan, Alexander Zipf, Martin Werner:
Semi-supervised Learning from Street-View Images and OpenStreetMap for Automatic Building Height Estimation. CoRR abs/2307.02574 (2023) - 2022
- [c4]Amir Raoofy, Gabriel Dax, Vittorio Serra, Max Ghiglione, Martin Werner, Carsten Trinitis:
Benchmarking and feasibility aspects of machine learning in space systems. CF 2022: 225-226 - 2021
- [c3]Gabriel Dax, Moritz Laass, Martin Werner:
Genetic Algorithm for Improved Transfer Learning Through Bagging Color-Adjusted Models. IGARSS 2021: 2612-2615 - [c2]Gabriel Dax, Martin Werner:
Trajectory Similarity using Compression. MDM 2021: 169-174 - 2020
- [c1]Martin Werner, Gabriel Dax, Moritz Laass:
Computational Challenges for Artificial Intelligence and Machine Learning in Environmental Research. GI-Jahrestagung 2020: 1009-1017
Coauthor Index
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last updated on 2024-09-04 01:20 CEST by the dblp team
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