Demonstrating EarthLake: A Model Lake System for Earth Observation Foundation Model Management
Summary: EarthLake is a model-lake system for Earth-observation foundation models, combining schema-guided registration, natural-language task discovery, and reproducible experiment management. It supports end-to-end model discovery, benchmarking, comparison, and deployment on new imagery. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Binger Chen (Humboldt University of Berlin)
- 2. Haralampos Gavriilidis (International Computer Science Institute; University of California Berkeley)
- 3. Luca Gaedicke (Berlin Institute for the Foundations of Learning and Data; Technical University of Berlin)
- 4. Tacettin Emre Bök (5U AI)
- 5. Matthias Boehm (Berlin Institute for the Foundations of Learning and Data; Technical University of Berlin)
- 6. Ziawasch Abedjan (Berlin Institute for the Foundations of Learning and Data; Technical University of Berlin)
- 7. Begüm Demir (Berlin Institute for the Foundations of Learning and Data; Technical University of Berlin)
- 8. Volker Markl (Berlin Institute for the Foundations of Learning and Data; Technical University of Berlin)
BibTeX Citation
@article{chen_vldb26,
title = {{Demonstrating EarthLake: A Model Lake System for Earth Observation Foundation Model Management}},
author = {Chen, Binger and Gavriilidis, Haralampos and Gaedicke, Luca and Bök, Tacettin Emre and Boehm, Matthias and Abedjan, Ziawasch and Demir, Begüm and Markl, Volker},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {12},
pages = {4610--4613},
doi = {10.14778/3827998.3828078},
url = {https://doi.org/10.14778/3827998.3828078},
year = {2026}
}
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| 5,792 | Optimizing Machine Learning Workloads in Collaborative Environments | 2020 | SIGMOD | 5.99349e-05 |
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