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GGLasso -- a Python package for General Graphical Lasso computation
Fabian Schaipp, Christian L. Müller, Oleg Vlasovets
We introduce GGLasso, a Python package for solving General Graphical Lasso problems. The Graphical Lasso scheme, introduced by (Friedman 2007) (see also (Yuan 2007; Banerjee 2008))…
Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks
Suryanarayana Maddu, Dominik Sturm, Christian L. Müller +1
We characterize and remedy a failure mode that may arise from multi-scale dynamics with scale imbalances during training of deep neural networks, such as Physics Informed Neural Ne…
deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression
David Rügamer, Chris Kolb, Cornelius Fritz +11
In this paper we describe the implementation of semi-structured deep distributional regression, a flexible framework to learn conditional distributions based on the combination of…
STENCIL-NET: Data-driven solution-adaptive discretization of partial differential equations
Suryanarayana Maddu, Dominik Sturm, Bevan L. Cheeseman +2
Numerical methods for approximately solving partial differential equations (PDE) are at the core of scientific computing. Often, this requires high-resolution or adaptive discretiz…