HAL (France)
open access
Sea surface salinity downscaling using deep generative diffusion models
High-resolution satellite observations are essential for studying fine-scale ocean processes. Yet, present satellite sea surface salinity (SSS) products remain too coarse to resolve many fine-scale structures. We investigate denoising diffusion models as a generative framework for SSS downscaling in
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Order-Optimal Sample Complexity of Rectified Flows#1232651
- Diffusion-Based Super-Resolution of Adriatic Sea Oceanographic Fields#1037257
- Learning Representations to Guide Pixel Diffusion Transformers#1297330
- Automated Subsurface Interpretation : Deep Learning Systems for Well Correlation and Reservoir Characterization#1166219
- Efficient Graph Generation via Direct Prediction and Flow Matching#1201410
Record · ID 1390391
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive