Effective Bayesian heteroscedastic regression with deep neural networks
Flexibly quantifying both irreducible aleatoric and model-dependent epistemic uncertainties
plays an important role for complex regression problems. While deep neural networks in …
plays an important role for complex regression problems. While deep neural networks in …
ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation
Modern climate projections lack adequate spatial and temporal resolution due to
computational constraints. A consequence is inaccurate and imprecise predictions of critical …
computational constraints. A consequence is inaccurate and imprecise predictions of critical …
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators
Modern climate projections lack adequate spatial and temporal resolution due to
computational constraints, leading to inaccuracies in representing critical processes like …
computational constraints, leading to inaccuracies in representing critical processes like …