If you’re looking for a standard boilerplate to analyse multivariate time-series data, this is for you! — In this post, I present standard steps that can be used for multivariate time series analysis, including application in forecasting. There are six steps that we will perform: 1. Causality Test 2. Cointegration Test 3. Stationarity Test and Make Stationary 4. Find optimal order p for VAR(p) 5. Residual Serial Correlation Test 6. Forecast and…

If you’re looking for a standard boilerplate to analyse univariate time-series data, this is for you! — In this post, I present standard steps that can be used for time series analysis, including application in forecasting. There are three steps that we will perform: 1. Check for Stationarity. Use 3 tests: ADF, KPSS and autocorrelation. 2. If signal is non-stationary, make it stationary. Use either transformation: Detrending, Differencing…

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

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? — 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…

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

This year marks the 17th anniversary of CUTEC. So I thought I’ll reach out to our former committees to see how they are doing and perhaps ask for a few thoughts on how the CUTEC experience, in hindsight, contributes to their life. The responses are surprisingly very encouraging! Do take…

I recently learned about Gaussian Process (GP) and how it can be used for regression. However, I have to admit that I had a hard time grasping the concept. It was only after I derived the equations and tried going through a few samples did I manage to start deciphering…

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…