Special session at Virtual ISF2020 on Global Modelling for Forecasting

Pablo Montero-Manso and I are organising an invited session at Virtual ISF2020 on Global Modelling for Forecasting. Details are here Speakers and topics are: Kasun Bandara (Speaker) Student, Monash University Transfer Learning Schemes for Global Forecasting Models using Recurrent Neural Networks Alexey Chernikov (Speaker) Student, Monash Automatic Feature-based Forecast Model Averaging Dilini Rajapaksha (Speaker) PhD Student, Monash University Local Model-Agnostic Interpretability in Global Time Series Forecasting

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Congratulations to my PhD students for their M5 success

A team of 4 Monash PhD students, three of whom I supervise (Kasun Bandara, Rakshitha Godahewa and Hansika Hewamalage) have achieved a 17th place in the M5 forecasting competition, with over 5000 participants. Congratulations!

Welcome to my new web page

Welcome to my new web page, I hope you find it useful and informative. It is based on hugo, blogdown, and I’m using the theme of my great colleague and mentor Rob J Hyndman.

Recent publications

  • Kasun Bandara, Christoph Bergmeir, Sam Campbell, Debbie Scott, Dan Lubman (2020) Towards Accurate Predictions and Causal `What-if' Analyses for Planning and Policy-making: A Case Study in Emergency Medical Services Demand. In: International Joint Conference on Neural Networks (IJCNN), 19 - 24 July, 2020, Glasgow (UK) (forthcoming). Abstract  pdf bib
  • Chang Wei Tan, Christoph Bergmeir, Francois Petitjean, Geoffrey I. Webb (2020) Time Series Regression. In: Working Paper. Abstract  pdf bib
  • Rakshitha Godahewa, Chang Deng, Arnaud Prouzeau, Christoph Bergmeir (2020) Simulation and Optimisation of Air Conditioning Systems using Machine Learning. In: Working Paper. Abstract  pdf bib
  • Rakshitha Godahewa, Trevor Yann, Christoph Bergmeir, Francois Petitjean (2020) Seasonal Averaged One-Dependence Estimators: A Novel Algorithm to Address Seasonal Concept Drift in High-Dimensional Stream Classification. In: International Joint Conference on Neural Networks (IJCNN), 19 - 24 July, 2020, Glasgow (UK) (forthcoming). Abstract  pdf bib
  • Hansika Hewamalage, Christoph Bergmeir, Kasun Bandara (2020) Recurrent Neural Networks for Time Series Forecasting: Current Status and Future Directions. In: International Journal of Forecasting, (forthcoming). Abstract  pdf bib

Recent and upcoming talks

  • ACML 2020 Tutorial: Forecasting for Data Scientists. (18 November 2020) More info...
  • Recurrent Neural Networks for Forecasting. (21 November 2019) More info...
  • How Machine Learning and Advanced Predictive Analytics Improves Demand Forecasting and Production Planning. (29 October 2019) More info...