A key numerical difficulty in compressible fluid dynamics is the formati...
Dense kernel matrices resulting from pairwise evaluations of a kernel
fu...
The theory of greedy low-rank learning (GLRL) aims to explain the impres...
To achieve scalable and accurate inference for latent Gaussian processes...
Physics Informed Neural Networks (PINNs) solve partial differential equa...
Many economic games and machine learning approaches can be cast as
compe...
Deep neural networks are usually initialized with random weights, with
a...
In this work, we show that solvers of elliptic boundary value problems i...
A multivariate distribution can be described by a triangular transport m...
Constrained competitive optimization involves multiple agents trying to
...
We propose to compute a sparse approximate inverse Cholesky factor L of ...
Generative adversarial networks (GANs) are capable of producing high qua...
We introduce a new algorithm for the numerical computation of Nash equil...
Power flow calculations for systems with a large number of buses, e.g. g...
Pandapower is a Python based, BSD-licensed power system analysis tool ai...