paper
2021
Explainability, uncertainty & physics
Hybrid physics-ML & parameterization New model or method
OtherMétéo-France (incl. CNRM) Journal
2021-04-06
051
Apr 2021
Blanka Balogh, David Saint‐Martin, Aurélien Ribes
Geophysical Research Letters
Météo-France (incl. CNRM)
An extended Lorenz-63 toy model reveals feedforward network instability, which training on Latin Hypercube samples removes, showing sampling design matters for stability.
Explainability, uncertainty & physics
A Toy Model to Investigate Stability of AI‐Based Dynamical Systems
In one sentence. An extended Lorenz-63 toy model reveals feedforward network instability, which training on Latin Hypercube samples removes, showing sampling design matters for stability.
Labels
- Topic
- Explainability, uncertainty & physics, Hybrid physics-ML & parameterization
- Type
- New model or method
- Method
- Other
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.1029/2020gl092133 OpenAlex:W3138927827
- Added
- 2026-10-22
Labels and summary are generated by Claude and reviewed weekly. Wrong? Edit this entry.