5 citations · 5 across the 13 of their papers we have counts for
4 papers · 1 filter
A Unifying Relational Perspective on Expressive Lottery Tickets
Lorenz Kummer, Samir Moustafa, Anatol Ehrlich +4
Graph neural networks (GNNs) are widely used, but how parameter sparsity affects the expressivity of relational (RGNNs) and temporal (TGNNs) variants is poorly understood. The Stro…
Parity, Sensitivity, and Transformers
Alexander Kozachinskiy, Tomasz Steifer, Przemysław Wałȩga
Understanding what neural architectures can and cannot compute is a central challenge in the theory of AI. One of the fundamental problems in this context is the PARITY task, which…
The Logical Expressiveness of Temporal GNNs via Two-Dimensional Product Logics
Marco Sälzer, Przemysław Andrzej Wałęga, Martin Lange
In recent years, the expressive power of various neural architectures -- including graph neural networks (GNNs), transformers, and recurrent neural networks -- has been characteris…
Expressive Power of Temporal Message Passing
Przemysław Andrzej Wałęga, Michael Rawson
Graph neural networks (GNNs) have recently been adapted to temporal settings, often employing temporal versions of the message-passing mechanism known from GNNs. We divide temporal…