Roberto Molinaro

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 16

Top Topics

Emission Tomography

Generalization Error

Inverse Problems

Top Venues

SIAM J. Numer. Anal.

Publications

Maximilian Herde, Bogdan Raonic, Tobias Rohner, Roger Käppeli, Roberto Molinaro, Emmanuel de Bézenac, Siddhartha Mishra
Poseidon: Efficient Foundation Models for PDEs. CoRR (2024)
Tim De Ryck, Siddhartha Mishra, Roberto Molinaro
wPINNs: Weak Physics Informed Neural Networks for Approximating Entropy Solutions of Hyperbolic Conservation Laws. SIAM J. Numer. Anal. 62 (2) (2024)
Roberto Molinaro, Yunan Yang, Björn Engquist, Siddhartha Mishra
Neural Inverse Operators for Solving PDE Inverse Problems. ICML (2023)
Francesca Bartolucci, Emmanuel de Bézenac, Bogdan Raonic, Roberto Molinaro, Siddhartha Mishra, Rima Alaifari
Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning. NeurIPS (2023)
Francesca Bartolucci, Emmanuel de Bézenac, Bogdan Raonic, Roberto Molinaro, Siddhartha Mishra, Rima Alaifari
Are Neural Operators Really Neural Operators? Frame Theory Meets Operator Learning. CoRR (2023)
Samuel Lanthaler, Roberto Molinaro, Patrik Hadorn, Siddhartha Mishra
Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities. ICLR (2023)
Bogdan Raonic, Roberto Molinaro, Tim De Ryck, Tobias Rohner, Francesca Bartolucci, Rima Alaifari, Siddhartha Mishra, Emmanuel de Bézenac
Convolutional Neural Operators for robust and accurate learning of PDEs. NeurIPS (2023)
Roberto Molinaro, Yunan Yang, Björn Engquist, Siddhartha Mishra
Neural Inverse Operators for Solving PDE Inverse Problems. CoRR (2023)
Bogdan Raonic, Roberto Molinaro, Tobias Rohner, Siddhartha Mishra, Emmanuel de Bézenac
Convolutional Neural Operators. CoRR (2023)
Samuel Lanthaler, Roberto Molinaro, Patrik Hadorn, Siddhartha Mishra
Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities. CoRR (2022)
Tim De Ryck, Siddhartha Mishra, Roberto Molinaro
wPINNs: Weak Physics informed neural networks for approximating entropy solutions of hyperbolic conservation laws. CoRR (2022)
Genming Bai, Ujjwal Koley, Siddhartha Mishra, Roberto Molinaro
Physics Informed Neural Networks (PINNs)for approximating nonlinear dispersive PDEs. CoRR (2021)
Siddhartha Mishra, Roberto Molinaro
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs II: A class of inverse problems. CoRR (2020)
Siddhartha Mishra, Roberto Molinaro
Physics Informed Neural Networks for Simulating Radiative Transfer. CoRR (2020)
Siddhartha Mishra, Roberto Molinaro
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs. CoRR (2020)
Kjetil O. Lye, Siddhartha Mishra, Roberto Molinaro
A Multi-level procedure for enhancing accuracy of machine learning algorithms. CoRR (2019)