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All these modelling decisions are handled by the initialisation functions in VERTEX, which also allow models to be initialised with uniform spatial connectivity profiles, no synapse reduction, arbitrary delay times, and in a cylindrical shape rather than the cuboid of our slice model.
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Simply put, models are initialised with random weights, and example inputs are fed through the network.
Simulations were initialised with the species occupying 20% of the landscape and run for 100 years.
The model was initialised with boundary conditions from the USGS PRISM2 data set and a Pliocene atmospheric CO2 level of 400 ppmv and run for 300 simulated years.
The model is initialised with atmospheric, oceanic, and sea-ice observational data and current anthropogenic and natural forcings, so that the simulations are representative of current real world climate.
To this purpose, the model was initialised with temperature and wind speed profiles from the meteorological soundings registered at Grand Junction station, located 300 km upwind of Boulder.
Weights for the system are initialised with pseudorandom numbers.
In addition, the system is initialised with a uniform initial condition of 0 for Q.
Parameters as in Fig. 2 and the system is initialised with a localised region of hyperpolarisation.
Specifically, the G-N approach is initialised with each initial candidate location.
According to this greedy algorithm, a tree is initialised with an arbitrary vertex.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com