Vignesh Gopakumar

According to our database, Vignesh Gopakumar authored at least 14 papers between 2020 and 2026.

Collaborative distances:

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

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

Leveraging AI modelling for FDS with Simvue: monitor and optimise for more sustainable simulations.

James Panayis, Matt Field, Vignesh Gopakumar, Andrew Lahiff, Kristian Zarebski, Aby Abraham, Jonathan L. Hodges

CoRR, September, 2025

Guaranteed confidence-band enclosures for PDE surrogates.

Ander Gray, Vignesh Gopakumar, Sylvain Rousseau, Sébastien Destercke

CoRR, January, 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

Guaranteed Prediction Sets for Functional Surrogate Models.

Ander Gray, Vignesh Gopakumar, Sylvain Rousseau, Sébastien Destercke

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 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

Fast regression of the tritium breeding ratio in fusion reactors.

Petr Mánek, Graham W. Van Goffrier, Vignesh Gopakumar, Nikolaos Nikolaou, Jonathan Shimwell, Ingo P. Waldmann

Mach. Learn. Sci. Technol., March, 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

Shaping of Magnetic Field Coils in Fusion Reactors using Bayesian Optimisation.

Timothy Nunn, Vignesh Gopakumar, Sebastien Kahn

CoRR, 2023

Fourier-RNNs for Modelling Noisy Physics Data.

Vignesh Gopakumar, Stanislas Pamela, Lorenzo Zanisi

CoRR, 2023

2022

Loss Landscape Engineering via Data Regulation on PINNs.

Vignesh Gopakumar, Stanislas Pamela, Debasmita Samaddar

CoRR, 2022

2020

Image mapping the temporal evolution of edge characteristics in tokamaks using neural networks.

Vignesh Gopakumar, D. Samaddar

Mach. Learn. Sci. Technol., 2020