Multimodel ensemble analysis with neural network Gaussian processes
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Publication:6138650
DOI10.1214/23-aoas1768arXiv2202.04152OpenAlexW4388075235MaRDI QIDQ6138650
Bo Li, Ryan Sriver, Unnamed Author
Publication date: 16 January 2024
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2202.04152
Cites Work
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- Improving predictive inference under covariate shift by weighting the log-likelihood function
- Deep learning: a Bayesian perspective
- Climate projections using Bayesian model averaging and space-time dependence
- Second-Order Exchangeability Analysis for Multimodel Ensembles
- Exploiting strength, discounting weakness: combining information from multiple climate simulators
- Modeling Nonstationary Processes Through Dimension Expansion
- On Constraining Projections of Future Climate Using Observations and Simulations From Multiple Climate Models
- Bayesian Modeling of Uncertainty in Ensembles of Climate Models
- Strictly Proper Scoring Rules, Prediction, and Estimation
- Probabilistic Forecasts, Calibration and Sharpness
- Modeling Nonstationarity in Space and Time
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