26 citations · 57 across the 20 of their papers we have counts for
23 papers
Beyond Accuracy: Assessing Calibration of Geospatial Foundation Models and Their Sensitivity to Distribution Shifts
Nils Lehmann, Jakob Gawlikowski, Burak Ekim +2
Geospatial Foundation Models (GeoFMs) are most commonly ranked and selected by accuracy on standard benchmark conditions via averaged ranks. We show that this protocol is too narro…
Earth Embeddings
Adam J. Stewart, Heng Fang, Isaac A. Corley +1
Earth observation is moving from foundation models that users must run themselves toward embedding products that package model feature outputs as reusable data without needing to d…
RSGPNet: Geometric Prompting for Remote Sensing Open-Vocabulary Semantic Segmentation
Shanwen Wang, Xin Sun, Sirui Wang +1
Open-vocabulary semantic segmentation (OVSS) enables text-guided segmentation of unseen objects, breaking fixed-class limitations to achieve open-world understanding. However, exis…
Agentic AI for Remote Sensing: Technical Challenges and Research Directions
Muhammad Akhtar Munir, Muhammad Umer Sheikh, Akashah Shabbir +5
Earth Observation (EO) is moving beyond static prediction toward multi-step analytical workflows that require coordinated reasoning over data, tools, and geospatial state. While fo…
SpectralEarth-FM: Bringing Hyperspectral Imagery into Multimodal Earth Observation Pretraining
Nassim Ait Ali Braham, Aaron Banze, Conrad M. Albrecht +3
Earth observation (EO) foundation models (FMs) are increasingly trained on multisensor data, spanning multispectral imagery (MSI), synthetic aperture radar (SAR), and derived geosp…
Bias-Constrained Diffusion Schedules for PDE Emulations: Reconstruction Error Minimization and Efficient Unrolled Training
Constantin Le Cleï, Nils Thuerey, Xiaoxiang Zhu
Conditional Diffusion Models are powerful surrogates for emulating complex spatiotemporal dynamics, yet they often fail to match the accuracy of deterministic neural emulators for…