Lorenzo Zanisi

According to our database, Lorenzo Zanisi authored at least 11 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Data-Efficient Neural Operator Training via Physics-Based Active Learning.

Alicja Polanska, Lorenzo Zanisi, Vignesh Gopakumar, Stanislas Pamela

CoRR, May, 2026

Learning Physical Operators using Neural Operators.

Vignesh Gopakumar, Ander Gray, Daniel Giles, Lorenzo Zanisi, Matt J. Kusner, Timo Betcke, Stanislas Pamela, Marc Peter Deisenroth

CoRR, February, 2026

2025

GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations.

Fabian Paischer, Gianluca Galletti, William Hornsby, Paul Setinek, Lorenzo Zanisi, Naomi Carey, Stanislas Pamela, Johannes Brandstetter

CoRR, October, 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, July, 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, February, 2025

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, Daniel Giles, Matt J. Kusner, Stanislas Pamela, Marc Peter Deisenroth

Proceedings of the Forty-second International Conference on Machine Learning, 2025

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

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

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, MAST Team

CoRR, 2023

Fourier-RNNs for Modelling Noisy Physics Data.

Vignesh Gopakumar, Stanislas Pamela, Lorenzo Zanisi

CoRR, 2023