Fourier-RNNs for Modelling Noisy Physics Data. - Vignesh Gopakumar; Stanislas Pamela; Lorenzo Zanisi (CoRR, 2023)

Plasma Surrogate Modelling using Fourier Neural Operators. - Vignesh Gopakumar; Stanislas Pamela; Lorenzo Zanisi; Zongyi Li; Ander Gray; Daniel Brennand; Nitesh Bhatia; Gregory Stathopoulos; Matt J. Kusner; Marc Peter Deisenroth; Anima Anandkumar; JOREK Team; et al. (CoRR, 2023)

Valid Error Bars for Neural Weather Models using Conformal Prediction. - Vignesh Gopakumar; Joel Oskarrson; Ander Gray; Lorenzo Zanisi; Stanislas Pamela; Daniel Giles; Matt J. Kusner; Marc Peter Deisenroth (CoRR, 2024)

Uncertainty Quantification of Pre-Trained and Fine-Tuned Surrogate Models using Conformal Prediction. - Vignesh Gopakumar; Ander Gray; Joel Oskarsson; Lorenzo Zanisi; Stanislas Pamela; Daniel Giles; Matt J. Kusner; Marc Peter Deisenroth (CoRR, 2024)

Neural-Parareal: Self-improving acceleration of fusion MHD simulations using time-parallelisation and neural operators. - Stanislas Pamela; Naomi Carey; Johannes Brandstetter; Rob J. Akers; Lorenzo Zanisi; James Buchanan; Vignesh Gopakumar; Matthias Hoelzl; Guido Huijsmans; Kamran Pentland; James Tickner; G. Antonucci (Comput. Phys. Commun., 2025)

Calibrated Physics-Informed Uncertainty Quantification. - Vignesh Gopakumar; Ander Gray; Lorenzo Zanisi; Timothy Nunn; Stanislas Pamela; Daniel Giles; Matt J. Kusner; Marc Peter Deisenroth (CoRR, 2025)

5D Neural Surrogates for Nonlinear Gyrokinetic Simulations of Plasma Turbulence. - Gianluca Galletti; Fabian Paischer; Paul Setinek; William Hornsby; Lorenzo Zanisi; Naomi Carey; Stanislas Pamela; Johannes Brandstetter (CoRR, 2025)

Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models. - Aaron Ho; Lorenzo Zanisi; Bram de Leeuw; Vincent Galvan; Pablo Rodriguez-Fernandez; Nathaniel T. Howard (CoRR, 2025)