Rafael Bischof – Medium

Rafael Bischof

Published in
Towards Data Science

4 Ideas for Physics-Informed Neural Networks that failed

Here is a list of extensions for PINNs that either did not improve their performance, or broke them completely — so you do not have to try…

Feb 11, 2023

4 Ideas for Physics-Informed Neural Networks that failed

Feb 11, 2023

Published in
Towards Data Science

10 Useful Hints and Tricks for Improving Physics-Informed Neural Networks (PINNs)

A handful of tricks concerning the sampling, architecture, activation function, loss balancing, optimisers, data normalisation, and more.

Feb 8, 2023

10 Useful Hints and Tricks for Improving Physics-Informed Neural Networks (PINNs)

Feb 8, 2023

AI-Augmented Designing Process of a Pedestrian Bridge in Switzerland

Leveraging AI to enhance designing processes in the AEC Industry: A Case Study of a Pedestrian Bridge in Switzerland

Feb 6, 2023

AI-Augmented Designing Process of a Pedestrian Bridge in Switzerland

Feb 6, 2023

Published in
Towards Data Science

Mixture of Experts for PINNs (MoE-PINNs)

Utilising Ensembles to enhance Physics-Informed Neural Networks

Feb 2, 2023

Mixture of Experts for PINNs (MoE-PINNs)

Feb 2, 2023

Published in
Towards Data Science

Improving Physics-Informed Neural Networks through Adaptive Loss Balancing

How to boost your PINN’s performance with ReLoBRaLo, Learning Rate Annealing and co.

Jan 31, 2023

Improving Physics-Informed Neural Networks through Adaptive Loss Balancing

Jan 31, 2023

Rafael Bischof

Rafael Bischof

My research focuses on leveraging machine learning to solve engineering challenges and incorporating prior domain knowledge to improve performance..

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