3 citations · 17 across the 14 of their papers we have counts for
15 papers
Graph Rewriting for Graph Neural Networks
Adam Machowczyk, Reiko Heckel
Given graphs as input, Graph Neural Networks (GNNs) support the inference of nodes, edges, attributes, or graph properties. Graph Rewriting investigates the rule-based manipulation…
Stochastic Decision Petri Nets
Florian Wittbold, Rebecca Bernemann, Reiko Heckel +2
We introduce stochastic decision Petri nets (SDPNs), which are a form of stochastic Petri nets equipped with rewards and a control mechanism via the deactivation of controllable tr…
Proceedings of the Thirteenth International Workshop on Graph Computation Models
Reiko Heckel, Christopher M. Poskitt
This volume contains the post-proceedings of the Thirteenth International Workshop on Graph Computation Models (GCM 2022). The workshop took place in Nantes, France on 6th July 202…
Cross-Skeleton Interaction Graph Aggregation Network for Representation Learning of Mouse Social Behaviour
Feixiang Zhou, Xinyu Yang, Fang Chen +7
Automated social behaviour analysis of mice has become an increasingly popular research area in behavioural neuroscience. Recently, pose information (i.e., locations of keypoints o…
Stochastic Graph Transformation For Social Network Modeling
Nicolas Behr, Bello Shehu Bello, Sebastian Ehmes +1
Adaptive networks model social, physical, technical, or biological systems as attributed graphs evolving at the level of both their topology and data. They are naturally described…
Encoding Incremental NACs in Safe Graph Grammars using Complementation
Andrea Corradini, Maryam Ghaffari Saadat, Reiko Heckel
In modelling complex systems with graph grammars (GGs), it is convenient to restrict the application of rules using attribute constraints and negative application conditions (NACs)…
Uncertainty Reasoning for Probabilistic Petri Nets via Bayesian Networks
Rebecca Bernemann, Benjamin Cabrera, Reiko Heckel +1
This paper exploits extended Bayesian networks for uncertainty reasoning on Petri nets, where firing of transitions is probabilistic. In particular, Bayesian networks are used as s…
Efficient Computation of Graph Overlaps for Rule Composition: Theory and Z3 Prototyping
Nicolas Behr, Reiko Heckel, Maryam Ghaffari Saadat
Graph transformation theory relies upon the composition of rules to express the effects of sequences of rules. In practice, graphs are often subject to constraints, ruling out many…
Analysis of Graph Transformation Systems: Native vs Translation-based Techniques
Reiko Heckel, Leen Lambers, Maryam Ghaffari Saadat
The paper summarises the contributions in a session at GCM 2019 presenting and discussing the use of native and translation-based solutions to common analysis problems for Graph Tr…
Updating Probabilistic Knowledge on Condition/Event Nets using Bayesian Networks
Benjamin Cabrera, Tobias Heindel, Reiko Heckel +1
The paper extends Bayesian networks (BNs) by a mechanism for dynamic changes to the probability distributions represented by BNs. One application scenario is the process of knowled…
Features of Agent-based Models
Reiko Heckel, Alexander Kurz, Edmund Chattoe-Brown
The design of agent-based models (ABMs) is often ad-hoc when it comes to defining their scope. In order for the inclusion of features such as network structure, location, or dynami…
Detecting and Refactoring Operational Smells within the Domain Name System
Marwan Radwan, Reiko Heckel
The Domain Name System (DNS) is one of the most important components of the Internet infrastructure. DNS relies on a delegation-based architecture, where resolution of names to the…
Resource-Bound Quantification for Graph Transformation
Paolo Torrini, Reiko Heckel
Graph transformation has been used to model concurrent systems in software engineering, as well as in biochemistry and life sciences. The application of a transformation rule can b…
Modeling and Reasoning over Distributed Systems using Aspect-Oriented Graph Grammars
Rodrigo Machado, Reiko Heckel, Leila Ribeiro
Aspect-orientation is a relatively new paradigm that introduces abstractions to modularize the implementation of system-wide policies. It is based on a composition operation, calle…
Towards an embedding of Graph Transformation in Intuitionistic Linear Logic
Paolo Torrini, Reiko Heckel
Linear logics have been shown to be able to embed both rewriting-based approaches and process calculi in a single, declarative framework. In this paper we are exploring the embeddi…