Efficient and effective analytics for real-world time series forecasting

Research output

Research output per year 2020 2020 2021 2022 2023 2024

• 16 Article
• 2 Conference Paper

Research output per year

Research output per year

Search results

• 2024

  Deep Active Audio Feature Learning in Resource-Constrained Environments

  Mohaimenuzzaman, M., Bergmeir, C. & Meyer, B., 2024, In: IEEE/ACM Transactions on Audio Speech and Language Processing. 32, p. 3224-3237 14 p.

  Research output: Contribution to journal › Article › Research › peer-review
  2 Citations (Scopus)

• Probabilistic causal effect estimation with global neural network forecasting models

  Grecov, P., Prasanna, A. N., Ackermann, K., Campbell, S., Scott, D. A., Lubman, D. I. & Bergmeir, C., Apr 2024, In: IEEE Transactions on Neural Networks and Learning Systems. 35, 4, p. 4999-5013 15 p.

  Research output: Contribution to journal › Article › Research › peer-review
  6 Citations (Scopus)
• 2023

  Adaptive dependency learning graph neural networks

  Sriramulu, A., Fourrier, N. & Bergmeir, C., May 2023, In: Information Sciences. 625, p. 700-714 15 p.

  Research output: Contribution to journal › Article › Research › peer-review
  23 Citations (Scopus)

• An accurate and fully-automated ensemble model for weekly time series forecasting

  Godahewa, R., Bergmeir, C., Webb, G. I. & Montero-Manso, P., Apr 2023, In: International Journal of Forecasting. 39, 2, p. 641-658 18 p.

  Research output: Contribution to journal › Article › Research › peer-review
  7 Citations (Scopus)

• Environmental sound classification on the edge: a pipeline for deep acoustic networks on extremely resource-constrained devices

  Mohaimenuzzaman, M., Bergmeir, C., West, I. & Meyer, B., Jan 2023, In: Pattern Recognition. 133, 12 p., 109025.

  Research output: Contribution to journal › Article › Research › peer-review
  45 Citations (Scopus)

• Forecast evaluation for data scientists: common pitfalls and best practices

  Hewamalage, H., Ackermann, K. & Bergmeir, C., 2023, In: Data Mining and Knowledge Discovery. 37, p. 788-832 45 p.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access

  File
  71 Citations (Scopus)

• LoMEF: a framework to produce local explanations for global model time series forecasts

  Rajapaksha, D., Bergmeir, C. & Hyndman, R. J., Jul 2023, In: International Journal of Forecasting. 39, 3, p. 1424-1447 24 p.

  Research output: Contribution to journal › Article › Research › peer-review
  6 Citations (Scopus)

• SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting

  Godahewa, R., Webb, G. I., Schmidt, D. & Bergmeir, C., Jul 2023, In: Machine Learning. 112, p. 2555–2591 37 p.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access

  File
  6 Citations (Scopus)
• 2022

  Global models for time series forecasting: a simulation study

  Hewamalage, H., Bergmeir, C. & Bandara, K., Apr 2022, In: Pattern Recognition. 124, 17 p., 108441.

  Research output: Contribution to journal › Article › Research › peer-review
  50 Citations (Scopus)

• Pruning vs XNOR-Net: A Comprehensive Study of Deep Learning for Audio Classification on Edge-devices

  Mohaimenuzzaman, M., Bergmeir, C. & Meyer, B., 6 Jan 2022, In: IEEE Access. 10, p. 6696-6707 12 p.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access
  22 Citations (Scopus)

• RNN-BOF: a multivariate global recurrent neural network for binary outcome forecasting of inpatient aggression

  Quinn, A., Simmons, M., Spivak, B. & Bergmeir, C., 2022, 2022 International Joint Conference on Neural Networks, IJCNN 2022 - Proceedings. Gori, M. & Sperduti, A. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 8 p. (Proceedings of the International Joint Conference on Neural Networks; vol. 2022-July).

  Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

• SQAPlanner: generating data-informed software quality improvement plans

  Rajapaksha, D., Tantithamthavorn, C., Jiarpakdee, J., Bergmeir, C., Grundy, J. & Buntine, W., 1 Aug 2022, In: IEEE Transactions on Software Engineering. 48, 8, p. 2814-2835 24 p.

  Research output: Contribution to journal › Article › Research › peer-review
  20 Citations (Scopus)
• 2021

  Ensembles of localised models for time series forecasting

  Godahewa, R., Bandara, K., Webb, G. I., Smyl, S. & Bergmeir, C., 5 Dec 2021, In: Knowledge-Based Systems. 233, 17 p., 107518.

  Research output: Contribution to journal › Article › Research › peer-review
  35 Citations (Scopus)

• Improving the accuracy of global forecasting models using time series data augmentation

  Bandara, K., Hewamalage, H., Liu, Y. H., Kang, Y. & Bergmeir, C., Dec 2021, In: Pattern Recognition. 120, 15 p., 108148.

  Research output: Contribution to journal › Article › Research › peer-review
  101 Citations (Scopus)

• LSTM-MSNet: leveraging forecasts on sets of related time series with multiple seasonal patterns

  Bandara, K., Bergmeir, C. & Hewamalage, H., Apr 2021, In: IEEE Transactions on Neural Networks and Learning Systems. 32, 4, p. 1586-1599 14 p.

  Research output: Contribution to journal › Article › Research › peer-review
• 2020

  LoRMIkA: Local Rule-based Model interpretability with k-optimal associations

  Rajapaksha, D., Bergmeir, C. & Buntine, W., Nov 2020, In: Information Sciences. 540, p. 221-241 21 p.

  Research output: Contribution to journal › Article › Research › peer-review
  26 Citations (Scopus)

• Recurrent Neural Networks for time series forecasting: current status and future directions

  Hewamalage, H., Bergmeir, C. & Bandara, K., Jan 2020, In: International Journal of Forecasting. 37, 1, p. 388-427 40 p.

  Research output: Contribution to journal › Article › Research › peer-review
  788 Citations (Scopus)

• Towards accurate predictions and causal 'What-if' analyses for planning and policy-making: a case study in Emergency Medical Services demand

  Bandara, K., Bergmeir, C., Campbell, S., Scott, D. & Lubman, D., 2020, 2020 International Joint Conference on Neural Networks (IJCNN), 2020 Conference Proceedings2020 International Joint Conference on Neural Networks, IJCNN 2020 - Proceedings. Roy, A. (ed.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 1887-1896 10 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
  9 Citations (Scopus)