Search Results for author: Tobias Rohner

Found 2 papers, 2 papers with code

Poseidon: Efficient Foundation Models for PDEs

3 code implementations29 May 2024 Maximilian Herde, Bogdan Raonić, Tobias Rohner, Roger Käppeli, Roberto Molinaro, Emmanuel de Bézenac, Siddhartha Mishra

Moreover, Poseidon scales with respect to model and data size, both for pretraining and for downstream tasks.

Convolutional Neural Operators for robust and accurate learning of PDEs

2 code implementations NeurIPS 2023 Bogdan Raonić, Roberto Molinaro, Tim De Ryck, Tobias Rohner, Francesca Bartolucci, Rima Alaifari, Siddhartha Mishra, Emmanuel de Bézenac

Although very successfully used in conventional machine learning, convolution based neural network architectures -- believed to be inconsistent in function space -- have been largely ignored in the context of learning solution operators of PDEs.

Operator learning PDE Surrogate Modeling

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