Nils Lehmann

According to our database, Nils Lehmann authored at least 13 papers between 2008 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

No One Knows the State of the Art in Geospatial Foundation Models.

Isaac Corley, Nils Lehmann, Caleb Robinson, Gabriel Tseng, Anthony Fuller, Hamed Alemohammad, Evan Shelhamer, Jennifer Marcus, Hannah Kerner

CoRR, May, 2026

Advancing Earth Observation Through Machine Learning: A TorchGeo Tutorial.

Caleb Robinson, Nils Lehmann, Adam J. Stewart, Burak Ekim, Heng Fang, Isaac A. Corley, Mauricio Cordeiro

CoRR, March, 2026

EO-VAE: Towards A Multi-sensor Tokenizer for Earth Observation Data.

Nils Lehmann, Yi Wang, Zhitong Xiong, Xiao Xiang Zhu

CoRR, February, 2026

2025

GEO-Bench-2: From Performance to Capability, Rethinking Evaluation in Geospatial AI.

Naomi Simumba, Nils Lehmann, Paolo Fraccaro, Hamed Alemohammad, Geeth De Mel, Salman H. Khan, Manil Maskey, Nicolas Longépé, Xiao Xiang Zhu, Hannah Kerner, Juan Bernabé-Moreno, Alexander Lacoste

CoRR, November, 2025

GeoLangBind: Unifying Earth Observation with Agglomerative Vision-Language Foundation Models.

Zhitong Xiong, Yi Wang, Weikang Yu, Adam J. Stewart, Jie Zhao, Nils Lehmann, Thomas Dujardin, Zhenghang Yuan, Pedram Ghamisi, Xiao Xiang Zhu

CoRR, March, 2025

Lightning UQ Box: Uncertainty Quantification for Neural Networks.

Nils Lehmann, Nina Maria Gottschling, Jakob Gawlikowski, Adam J. Stewart, Stefan Depeweg, Eric T. Nalisnick

J. Mach. Learn. Res., 2025

Panopticon: Advancing Any-Sensor Foundation Models for Earth Observation.

Leonard Waldmann, Ando Shah, Yi Wang, Nils Lehmann, Adam J. Stewart, Zhitong Xiong, Xiao Xiang Zhu, Stefan Bauer, John Chuang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

2024

Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning.

Nils Lehmann, Jakob Gawlikowski, Adam J. Stewart, Vytautas Jancauskas, Stefan Depeweg, Eric T. Nalisnick, Nina Maria Gottschling

CoRR, 2024

Uncertainty Aware Tropical Cyclone Wind Speed Estimation from Satellite Data.

Nils Lehmann, Nina Maria Gottschling, Stefan Depeweg, Eric T. Nalisnick

CoRR, 2024

Seismic Monitoring and Analysis Challenge (SMAC) Report.

Daniele Rege Cambrin, Lorenzo Vaiani, Isaac Corley, Nils Lehmann, Giorgio Morales, Pascal Tribel

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2024

2023

SSL4EO-L: Datasets and Foundation Models for Landsat Imagery.

Adam J. Stewart, Nils Lehmann, Isaac A. Corley, Yi Wang, Yi-Chia Chang, Nassim Ait Ali Braham, Shradha Sehgal, Caleb Robinson, Arindam Banerjee

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GEO-Bench: Toward Foundation Models for Earth Monitoring.

Alexandre Lacoste, Nils Lehmann, Pau Rodríguez, Evan D. Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vázquez, Dava J. Newman, Yoshua Bengio, Stefano Ermon, Xiaoxiang Zhu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2008

Reliability of diagnoses coding with ICD-10.

Jürgen Stausberg, Nils Lehmann, Dirk Kaczmarek, Markus Stein

Int. J. Medical Informatics, 2008