Hope: High-order graph ode for modeling interacting dynamics
Leading graph ordinary differential equation (ODE) models have offered generalized
strategies to model interacting multi-agent dynamical systems in a data-driven approach …
strategies to model interacting multi-agent dynamical systems in a data-driven approach …
De bruijn goes neural: Causality-aware graph neural networks for time series data on dynamic graphs
Abstract We introduce De Bruijn Graph Neural Networks (DBGNNs), a novel time-aware
graph neural network architecture for time-resolved data on dynamic graphs. Our approach …
graph neural network architecture for time-resolved data on dynamic graphs. Our approach …
Raphtory: The temporal graph engine for Rust and Python
Raphtory is a platform for building and analysing temporal networks. The library includes
methods for creating networks from a variety of data sources; algorithms to explore their …
methods for creating networks from a variety of data sources; algorithms to explore their …
[PDF][PDF] Phasik: a Python package to identify system states in partially temporal networks
Phasik is a Python library for analyzing the temporal structure of temporal and partially
temporal networks. Temporal networks are used to model complex systems that consist of …
temporal networks. Temporal networks are used to model complex systems that consist of …
One Graph to Rule them All: Using NLP and Graph Neural Networks to analyse Tolkien's Legendarium
Natural Language Processing and Machine Learning have considerably advanced
Computational Literary Studies. Similarly, the construction of co-occurrence networks of …
Computational Literary Studies. Similarly, the construction of co-occurrence networks of …
Report on the 11th international workshop on location and the web (LocWeb 2021) and the 11th temporal web analytics workshop (TempWeb2021) at WWW2021
LocWeb and TempWeb 2021 were the eleventh events in their workshop series and took
place co-located on 12th April 2021 in conjunction with The Web Conference WWW 2021 …
place co-located on 12th April 2021 in conjunction with The Web Conference WWW 2021 …
[PDF][PDF] Detecting and visualizing patterns in the causal topology of temporal networks
V Perri - 2023 - zora.uzh.ch
Complex systems are systems that, due to the intricacy of the relations between their (often
numerous) components, cannot be analyzed by reducing their behavior to that of their …
numerous) components, cannot be analyzed by reducing their behavior to that of their …
[PDF][PDF] Remote Participants
C Addington, N Arnold, H Aziz… - Coalition Formation …, 2021 - drops.dagstuhl.de
Two key changes are driving an immediate need for deeper understanding of I/O workloads
in highperformance computing (HPC): applications are evolving beyond the traditional bulk …
in highperformance computing (HPC): applications are evolving beyond the traditional bulk …
[PDF][PDF] 4.6 Visualisation and Interpretability of Higher-Order Networks
US Lafayette, L Qarkaxhija - Higher-Order Graph Models: From … - drops.dagstuhl.de
Acknowledging while looking to leverage our biases, we first highlighted the following most
relevant tools developed by participants in this Dagstuhl: pathpy [26] is a Python package …
relevant tools developed by participants in this Dagstuhl: pathpy [26] is a Python package …