COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring. |
University of Cambridge > Talks.cam > Artificial Intelligence Research Group Talks (Computer Laboratory) > Weisfeiler and Lehman Go Cellular: CW Networks
Weisfeiler and Lehman Go Cellular: CW NetworksAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Mateja Jamnik. Graph Neural Networks (GNNs) are limited in their expressive power, struggle with long-range interactions and lack a principled way to model higher-order structures. These problems can be attributed to the strong coupling between the computational graph and the input graph structure. The recently proposed Message Passing Simplicial Networks naturally decouple these elements by performing message passing on the clique complex of the graph. Nevertheless, these models can be severely constrained by the rigid combinatorial structure of Simplicial Complexes (SCs). In this work, we extend recent theoretical results on SCs to regular Cell Complexes, topological objects that flexibly subsume SCs and graphs. We show that this generalisation provides a powerful set of graph “lifting” transformations, each leading to a unique hierarchical message passing procedure. The resulting methods, which we collectively call CW Networks (CWNs), are strictly more powerful than the WL test and not less powerful than the 3-WL test. In particular, we demonstrate the effectiveness of one such scheme, based on rings, when applied to molecular graph problems. The proposed architecture benefits from provably larger expressivity than commonly used GNNs, principled modelling of higher-order signals and from compressing the distances between nodes. We demonstrate that our model achieves state-of-the-art results on a variety of molecular datasets. This talk is part of the Artificial Intelligence Research Group Talks (Computer Laboratory) series. This talk is included in these lists:
Note that ex-directory lists are not shown. |
Other listsReading Group on Stochastic Differential Equations CUFAS talks Cambridge Finance Workshop SeriesOther talksThe Anne McLaren Lecture: Embryonic and adult neural stem cells- what underlies their difference Statistics Clinic Lent 2022 II MAGNATM, a novel single molecule platform to analyze genetic variation and epigenetic modifications on native RNA and DNA molecules What does magic tell us about free will? Why Johnny doesn’t write secure software? Statistics Clinic Summer 2022 I |