We introduce MAESTRO, a tailored adaptation of the Masked Autoencoder (MAE) framework that effectively orchestrates the use of multimodal, multitemporal, and multispectral Earth Observation (EO) data.

Abstract: Masked autoencoders (MAE) is a deep learning method based on Transformer. Originally used for images, it has now been extended to video, audio, and some other temporal prediction tasks. In ...

Abstract: Deep learning (DL) methodology contributes a lot to the development of hyperspectral image (HSI) analysis community. However, it also makes HSI analysis systems vulnerable to adversarial ...

🧬 Extract SAE features from protein language models (PLMs) 📊 Analyze and interpret learned features through association with protein annotations 🎨 Visualize feature patterns and relationships 🤗 ...