Alberto Carrassi
Researcher / author (OpenAlex)
Facts
2 properties- Affiliation
- Bologna Observatory, INFN Sezione di Bologna, University of Reading, University of Bolognaas of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
🔖 Identifiers · 2
- ORCID iD
- 0000-0003-0722-5600
- OpenAlex ID
- A5018511252, A5134957370as of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 19
Accurate deep learning-based filtering for chaotic dynamics by identifying instabilities without an ensemble,
Arctic sea ice data assimilation combining an ensemble Kalman filter with a novel Lagrangian sea ice model for the winter 2019–2020,
Assimilation of Sentinel-1 Backscatter into a Land Surface Model with River Routing and Its Impact on Streamflow Simulations in Two Belgian Catchments,
Chaotic dynamics and the role of covariance inflation for reduced rank Kalman filters with model error,
Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: A case study with the Lorenz 96 model,
Combining data assimilation and machine learning to infer unresolved scale parametrization,
Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models,
Data assimilation by delay‐coordinate nudging
+11 more
← Authored by 19
Accurate deep learning-based filtering for chaotic dynamics by identifying instabilities without an ensemble,
Arctic sea ice data assimilation combining an ensemble Kalman filter with a novel Lagrangian sea ice model for the winter 2019–2020,
Assimilation of Sentinel-1 Backscatter into a Land Surface Model with River Routing and Its Impact on Streamflow Simulations in Two Belgian Catchments,
Chaotic dynamics and the role of covariance inflation for reduced rank Kalman filters with model error,
Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: A case study with the Lorenz 96 model,
Combining data assimilation and machine learning to infer unresolved scale parametrization,
Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models,
Data assimilation by delay‐coordinate nudging
+11 more
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Summary
Alberto Carrassi is a human[1].