Roberto Molinaro

21 papers A* 5Journal 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Universal Diffusion-Based Probabilistic Downscaling. CoRR Roberto Molinaro, Niall Siegenheim, Henry Martin, Mark Frey, Niels Poulsen, Philipp Seitz, Marvin Vincent Gabler
2025	J	`jnl`	EPT-2 Technical Report. CoRR Roberto Molinaro, Niall Siegenheim, Niels Poulsen, Jordan Dane Daubinet, Henry Martin, Mark Frey, Kevin Thiart, Alexander Jakob Dautel, Andreas Schlueter, Alex Grigoryev, Bogdan Danciu, Nikoo Ekhtiari, Bas Steunebrink, Leonie Wagner, Marvin Vincent Gabler
2024	J	`jnl`	EPT-1.5 Technical Report. CoRR Roberto Molinaro, Jordan Dane Daubinet, Alexander Jakob Dautel, Andreas Schlueter, Alex Grigoryev, Nikoo Ekhtiari, Bas Steunebrink, Kevin Thiart, Roan John Song, Henry Martin, Leonie Wagner, Andrea Giussani, Marvin Vincent Gabler
2024	J	`jnl`	Generative AI for fast and accurate Statistical Computation of Fluids. CoRR Roberto Molinaro, Samuel Lanthaler, Bogdan Raonic, Tobias Rohner, Victor Armegioiu, Zhong Yi Wan, Fei Sha, Siddhartha Mishra, Leonardo Zepeda-Núñez
2024	A*	`conf`	Poseidon: Efficient Foundation Models for PDEs. NeurIPS Maximilian Herde, Bogdan Raonic, Tobias Rohner, Roger Käppeli, Roberto Molinaro, Emmanuel de Bézenac, Siddhartha Mishra
2024	J	`jnl`	Poseidon: Efficient Foundation Models for PDEs. CoRR Maximilian Herde, Bogdan Raonic, Tobias Rohner, Roger Käppeli, Roberto Molinaro, Emmanuel de Bézenac, Siddhartha Mishra
2024	J	`jnl`	wPINNs: Weak Physics Informed Neural Networks for Approximating Entropy Solutions of Hyperbolic Conservation Laws. SIAM J. Numer. Anal. Tim De Ryck, Siddhartha Mishra, Roberto Molinaro
2023	J	`jnl`	Are Neural Operators Really Neural Operators? Frame Theory Meets Operator Learning. CoRR Francesca Bartolucci, Emmanuel de Bézenac, Bogdan Raonic, Roberto Molinaro, Siddhartha Mishra, Rima Alaifari
2023	A*	`conf`	Convolutional Neural Operators for robust and accurate learning of PDEs. NeurIPS Bogdan Raonic, Roberto Molinaro, Tim De Ryck, Tobias Rohner, Francesca Bartolucci, Rima Alaifari, Siddhartha Mishra, Emmanuel de Bézenac
2023	J	`jnl`	Convolutional Neural Operators. CoRR Bogdan Raonic, Roberto Molinaro, Tobias Rohner, Siddhartha Mishra, Emmanuel de Bézenac
2023	A*	`conf`	Neural Inverse Operators for Solving PDE Inverse Problems. ICML Roberto Molinaro, Yunan Yang, Björn Engquist, Siddhartha Mishra
2023	J	`jnl`	Neural Inverse Operators for Solving PDE Inverse Problems. CoRR Roberto Molinaro, Yunan Yang, Björn Engquist, Siddhartha Mishra
2023	A*	`conf`	Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities. ICLR Samuel Lanthaler, Roberto Molinaro, Patrik Hadorn, Siddhartha Mishra
2023	A*	`conf`	Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning. NeurIPS Francesca Bartolucci, Emmanuel de Bézenac, Bogdan Raonic, Roberto Molinaro, Siddhartha Mishra, Rima Alaifari
2022	J	`jnl`	Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities. CoRR Samuel Lanthaler, Roberto Molinaro, Patrik Hadorn, Siddhartha Mishra
2022	J	`jnl`	wPINNs: Weak Physics informed neural networks for approximating entropy solutions of hyperbolic conservation laws. CoRR Tim De Ryck, Siddhartha Mishra, Roberto Molinaro
2021	J	`jnl`	Physics Informed Neural Networks (PINNs)for approximating nonlinear dispersive PDEs. CoRR Genming Bai, Ujjwal Koley, Siddhartha Mishra, Roberto Molinaro
2020	J	`jnl`	Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs II: A class of inverse problems. CoRR Siddhartha Mishra, Roberto Molinaro
2020	J	`jnl`	Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs. CoRR Siddhartha Mishra, Roberto Molinaro
2020	J	`jnl`	Physics Informed Neural Networks for Simulating Radiative Transfer. CoRR Siddhartha Mishra, Roberto Molinaro
2019	J	`jnl`	A Multi-level procedure for enhancing accuracy of machine learning algorithms. CoRR Kjetil O. Lye, Siddhartha Mishra, Roberto Molinaro