143 citations · 757 across the 54 of their papers we have counts for
59 papers
Symmetry analysis and exact solutions of multi-layer quasi-geostrophic problem
Serhii D. Koval, Alex Bihlo, Roman O. Popovych
We carry out an extended symmetry analysis of the multi-layer quasi-geostrophic problem. This model is given by a system of an arbitrary number of coupled barotropic vorticity equa…
Improving physics-informed DeepONets with hard constraints
Rüdiger Brecht, Dmytro R. Popovych, Alex Bihlo +1
Current physics-informed (standard or deep operator) neural networks still rely on accurately learning the initial and/or boundary conditions of the system of differential equation…
Towards replacing precipitation ensemble predictions systems using machine learning
Rüdiger Brecht, Alex Bihlo
Precipitation forecasts are less accurate compared to other meteorological fields because several key processes affecting precipitation distribution and intensity occur below the r…
M-ENIAC: A machine learning recreation of the first successful numerical weather forecasts
Rüdiger Brecht, Alex Bihlo
In 1950 the first successful numerical weather forecast was obtained by solving the barotropic vorticity equation using the Electronic Numerical Integrator and Computer (ENIAC), wh…
Improving physics-informed neural networks with meta-learned optimization
Alex Bihlo
We show that the error achievable using physics-informed neural networks for solving systems of differential equations can be substantially reduced when these networks are trained…
Model-agnostic machine learning of conservation laws from data
Shivam Arora, Alex Bihlo, Rüdiger Brecht +1
We present a machine learning based method for learning first integrals of systems of ordinary differential equations from given trajectory data. The method is model-agnostic in th…