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cs.LG2024★ 1 cited
Defining error accumulation in ML atmospheric simulators
Raghul Parthipan, Mohit Anand, Hannah M. Christensen +2
Machine learning (ML) has recently shown significant promise in modelling atmospheric systems, such as the weather. Many of these ML models are autoregressive, and error accumulati…
cs.LG2023★ 1 cited
Taylorformer: Probabilistic Modelling for Random Processes including Time Series
Omer Nivron, Raghul Parthipan, Damon J. Wischik
We propose the Taylorformer for random processes such as time series. Its two key components are: 1) the LocalTaylor wrapper which adapts Taylor approximations (used in dynamical s…