Using Mutual Information to measure the likelihood of candidate links in a graph.

Image by Gerd Altmann from Pixabay

During my literature review, I stumbled upon an information-theoretic framework to analyse the link prediction problem (Tan et al. (2014), Kumar and Sharma (2020)). For an overview of what link prediction is, read my previous article here. The basic idea is to predict unseen edges in a graph. Such edges…

Making Sense of Big Data, Network Science

What’s the one common thing between finding colleagues in Linkedin, friends in Facebook, co-authors in Google Scholar, dates in Tinder, products recommendation in Amazon, new songs in Spotify, movies advice in Netflix, new suppliers in supply chain and interactions of gene/protein in a biological network?

Photo by ROBIN WORRALL on Unsplash

Answer: They can all be mathematically formulated as a graph link prediction problem!

In short, given a graph G (V, E) with |V| vertices and |E| edges, our task is to predict the existence of a previously unknown edge e_12 E between vertices v_1, v_2 V. We can…


I’ve recently been looking for an open-source, distributed graph database, as I need to store a large graph data somewhere persistently. My main requirement is that I’d like to have as much control as possible over the underlying storage and indexing system behind such aforementioned database.

I stumbled upon JanusGraph

Pada bulan Juni 2020 yang lalu, kami diundang oleh International Telecommunication Union untuk memberikan presentasi tentang peran Alva Energi di Indonesia dalam sebuah virtual conference tahunan yang bernama World Summit on the Information Society.

Dalam webinar tersebut, kami bercerita lebih tentang perkembangan energi terbarukan di Indonesia dan juga peran aktif yang telah kami lakukan selama ini. Rekaman webinar tersebut dapat diakses di website resmi WSIS berikut ini:

The following document provides a whirlwind tour of some fundamental concepts in geometric deep learning.

Photo by Clint Adair on Unsplash

Find the latex-written version of this article here

The following document provides a whirlwind tour of some fundamental concepts in geometric deep learning. The mathematical derivations might not be as rigorously shown and some equations are stated without proofs. This is done intentionally to keep the document short yet comprehensive…

Notice what’s common among the two? Both are queues! Image sources: and

Servitization is a phenomena where manufacturing firms shift from selling pure products to offering solutions (services) instead. Neely (2013) provides a brief introduction on how companies across industries are adopting this business model.

What’s interesting is that servitization also results in a less clear boundary between manufacturing and service firms…

This post is a summary of the theory of nonlinear dynamics and chaos that I have recently learned from an online course by the Santa Fe Institute. All materials are credited to the institute alone.

Dynamics is a branch of mathematics that studies how systems change over time. Up until…

Edward Elson Kosasih

Machine Learning | Network Science | Supply Chain and Manufacturing Analytics |

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