5 citations · 10 across the 18 of their papers we have counts for
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Accelerating Quasi-Static Time Series Simulations with Foundation Models
Alban Puech, François Mirallès, Jonas Weiss +5
Quasi-static time series (QSTS) simulations have great potential for evaluating the grid's ability to accommodate the large-scale integration of distributed energy resources. Howev…
Optimal Power Grid Operations with Foundation Models
Alban Puech, Jonas Weiss, Thomas Brunschwiler +1
The energy transition, crucial for tackling the climate crisis, demands integrating numerous distributed, renewable energy sources into existing grids. Along with climate change an…
Foundation Models for the Electric Power Grid
Hendrik F. Hamann, Thomas Brunschwiler, Blazhe Gjorgiev +24
Foundation models (FMs) currently dominate news headlines. They employ advanced deep learning architectures to extract structural information autonomously from vast datasets throug…
Neural Embedding Compression For Efficient Multi-Task Earth Observation Modelling
Carlos Gomes, Thomas Brunschwiler
As repositories of large scale data in earth observation (EO) have grown, so have transfer and storage costs for model training and inference, expending significant resources. We i…
Multi-Spectral Remote Sensing Image Retrieval Using Geospatial Foundation Models
Benedikt Blumenstiel, Viktoria Moor, Romeo Kienzler +1
Image retrieval enables an efficient search through vast amounts of satellite imagery and returns similar images to a query. Deep learning models can identify images across various…