activity
20162026
most citedGibbs-Helmholtz Graph Neural Network: capturing the temperature dependency of activity coefficients at infinite dilution

35 citations · 180 across the 39 of their papers we have counts for

collaborators
Showing 2019Show all

5 papers · 1 filter

math.NA2019

Solving differential Riccati equations: A nonlinear space-time method using tensor trains

Tobias Breiten, Sergey Dolgov, Martin Stoll

Differential algebraic Riccati equations are at the heart of many applications in control theory. They are time-depent, matrix-valued, and in particular nonlinear equations that re…

math.NA2019★ 24 cited

A literature survey of matrix methods for data science

Martin Stoll

Efficient numerical linear algebra is a core ingredient in many applications across almost all scientific and industrial disciplines. With this survey we want to illustrate that nu…

math.OC2019

Optimization of a partial differential equation on a complex network

Martin Stoll, Max Winkler

Differential equations on metric graphs can describe many phenomena in the physical world but also the spread of information on social media. To efficiently compute the solution is…

math.NA2019

Improved penalty algorithm for Mixed Integer PDE Constrained Optimization Problems

Dominik Garmatter, Margherita Porcelli, Francesco Rinaldi +1

Optimal control problems including partial differential equation (PDE) as well as integer constraints merge the combinatorial difficulties of integer programming and the challenges…

cs.LG2019★ 1 cited

Semi-Supervised Classification on Non-Sparse Graphs Using Low-Rank Graph Convolutional Networks

Dominik Alfke, Martin Stoll

Graph Convolutional Networks (GCNs) have proven to be successful tools for semi-supervised learning on graph-based datasets. For sparse graphs, linear and polynomial filter functio…