Data From "The capacity of generative models to synthesize regional landslide and non-landslide remote sensing imagery under data-scarce scenarios: insights from multimodal foundation models"

Landslide Susceptibility Mapping in Nigeria Using Remote Sensing, GIS, and Machine Learning Models

Landslide situations remain a significant concern in Nigeria, as they pose a great risk to human liv

Integrated landslide risk models to account for the human impact on landslide activity

Landslide risk will gradually increase in low- and lower-middle-incom

From data to currents: generative models for short-term forecasting of oceanic currents

A Modified Mask-RCNN Algorithm for Intelligent Identification of Landslide Based on High-resolution Remote Sensing data

<p>Deep learning is a data-driven approach that requires high-quality labeled data to

Spatially orthogonal factor models for spatial transcriptomics and remote sensing data

Principal component analyses are often applied to spatial data towards inference on latent modes of

From Rows to Yields: How Foundation Models for Tabular Data Simplify Crop Yield Prediction

We present an application of a foundation model for small- to medium-sized tabular data (TabPFN), to