24 citations · 27 across the 5 of their papers we have counts for
5 papers
Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaos
Chris Pedersen, Laure Zanna, Joan Bruna
Autoregressive surrogate models (or \textit{emulators}) of spatiotemporal systems provide an avenue for fast, approximate predictions, with broad applications across science and en…
Multi-scale decomposition of sea surface height snapshots using machine learning
Jingwen Lyu, Yue Wang, Christian Pedersen +2
Knowledge of ocean circulation is important for understanding and predicting weather and climate, and managing the blue economy. This circulation can be estimated through Sea Surfa…
Learnable wavelet neural networks for cosmological inference
Christian Pedersen, Michael Eickenberg, Shirley Ho
Convolutional neural networks (CNNs) have been shown to both extract more information than the traditional two-point statistics from cosmological fields, and marginalise over astro…
Reliable coarse-grained turbulent simulations through combined offline learning and neural emulation
Christian Pedersen, Laure Zanna, Joan Bruna +1
Integration of machine learning (ML) models of unresolved dynamics into numerical simulations of fluid dynamics has been demonstrated to improve the accuracy of coarse resolution s…
Compressing the cosmological information in one-dimensional correlations of the Lyman- forest
Christian Pedersen, Andreu Font-Ribera, Nickolay Y. Gnedin
Observations of the Lyman- (Ly) forest from spectroscopic surveys such as BOSS/eBOSS, or the ongoing DESI, offer a unique window to study the growth of structure on megaparse…