35 citations · 144 across the 25 of their papers we have counts for
Showing 2025Show all
3 papers · 1 filter
math.PR2025
Global universal approximation with Brownian signatures
Mihriban Ceylan, David J. Prömel
We establish -universal approximation theorems for general path-dependent and non-anticipative functionals on suitable rough path spaces, showing that linear functionals actin…
stat.ML2025
Distributionally robust approximation property of neural networks
Mihriban Ceylan, David J. Prömel
The universal approximation property uniformly with respect to weakly compact families of measures is established for several classes of neural networks. To that end, we prove that…
math.PR2025
Universal approximation property of neural stochastic differential equations
Anna P. Kwossek, David J. Prömel, Josef Teichmann
We identify various classes of neural networks that are able to approximate continuous functions locally uniformly subject to fixed global linear growth constraints. For such neura…