paper
2018
Software, scaling & compression
Benchmarks, datasets & evaluation Evaluation or intercomparison of existing models
Classical ML (trees, GP, linear, kernels) Journal
2018-12-01
004
Dec 2018
Shreya Mahajan -, Katherine J. Evans, James H. Kennedy
AGUFM
AGU abstract-less entry applying machine learning to assess reproducibility of climate model simulations across hybrid HPC architectures.
Software, scaling & compression
Machine Learning techniques to evaluate reproducibility of climate model simulations on hybrid architectures.
In one sentence. AGU abstract-less entry applying machine learning to assess reproducibility of climate model simulations across hybrid HPC architectures.
Labels
- Topic
- Software, scaling & compression, Benchmarks, datasets & evaluation
- Type
- Evaluation or intercomparison of existing models
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Global
- Data
- CMIP / climate model output
- Status
- Research
- Identifiers
- OpenAlex:W3045416016
- Added
- 2026-10-22
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