15 citations · 40 across the 6 of their papers we have counts for
6 papers
GAETS: A Graph Autoencoder Time Series Approach Towards Battery Parameter Estimation
Edward Elson Kosasih, Rucha Bhalchandra Joshi, Janamejaya Channegowda
Lithium-ion batteries are powering the ongoing transportation electrification revolution. Lithium-ion batteries possess higher energy density and favourable electrochemical propert…
Data Considerations in Graph Representation Learning for Supply Chain Networks
Ajmal Aziz, Edward Elson Kosasih, Ryan-Rhys Griffiths +1
Supply chain network data is a valuable asset for businesses wishing to understand their ethical profile, security of supply, and efficiency. Possession of a dataset alone however…
Supply Chain Digital Twin Framework Design: An Approach of Supply Chain Operations Reference Model and System of Systems
Jie Zhang, Alexandra Brintrup, Anisoara Calinescu +2
Digital twin technology has been regarded as a beneficial approach in supply chain development. Different from traditional digital twin (temporal dynamic), supply chain digital twi…
Reinforcement Learning Provides a Flexible Approach for Realistic Supply Chain Safety Stock Optimisation
Edward Elson Kosasih, Alexandra Brintrup
Although safety stock optimisation has been studied for more than 60 years, most companies still use simplistic means to calculate necessary safety stock levels, partly due to the…
On Graph Neural Network Ensembles for Large-Scale Molecular Property Prediction
Edward Elson Kosasih, Joaquin Cabezas, Xavier Sumba +5
In order to advance large-scale graph machine learning, the Open Graph Benchmark Large Scale Challenge (OGB-LSC) was proposed at the KDD Cup 2021. The PCQM4M-LSC dataset defines a…
Digital Twins: State of the Art Theory and Practice, Challenges, and Open Research Questions
Angira Sharma, Edward Kosasih, Jie Zhang +2
Digital Twin was introduced over a decade ago, as an innovative all-encompassing tool, with perceived benefits including real-time monitoring, simulation and forecasting. However,…