Fotios Petropoulos

Management Science and Operations Research · 2011–2020

A researcher in the Science corpus: 19 papers; trusts 59 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Management Science and Operations Research — 359 citations into it; #1,466 of 11,946 by trust here, #913 by citations
• Economics and Econometrics — 305 citations into it; #12,509 of 23,481 by trust here, #10,386 by citations
• Statistics and Probability — 157 citations into it
• Finance — 118 citations into it
• Time-Series & Forecasting — 111 citations into it
• Artificial Intelligence — 93 citations into it
• Evaluation & Benchmarks — 68 citations into it
• Electrical and Electronic Engineering — 67 citations into it

Whom Fotios Petropoulos trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Rob J Hyndman
2. Spyros Makridakis
3. Vassilios Assimakopoulos
4. M. Hibon
5. Stephan Kolassa
6. A. Syntetos
7. James W. Taylor
8. Nikolaos Kourentzes
9. Anne B. Koehler
10. Leo Breiman

Who trusts Fotios Petropoulos overall

1. Evangelos Spiliotis
2. Spyros Makridakis
3. Vassilios Assimakopoulos
4. Konstantinos Nikolopoulos
5. Rob J Hyndman
6. V. Sharma
7. Xiaoqian Wang
8. Christoph Bergmeir
9. Furqan Rustam
10. U. Nigam

Papers from Fotios Petropoulos's perspective

Ordered by how strongly the researchers Fotios Petropoulos trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Regression Shrinkage and Selection via the Lasso
3. Estimating the Dimension of a Model
4. Bagging Predictors
5. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation
6. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
7. Generalized autoregressive conditional heteroskedasticity
8. The Elements of Statistical Learning
9. Combining forecasts: A review and annotated bibliography
10. Asymptotic Inference about Predictive Ability

Their papers

• Forecasting with temporal hierarchies (2017) — 268 citations
• Improving forecasting by estimating time series structural components across multiple frequencies (2014) — 188 citations
• Exploring the sources of uncertainty: Why does bagging for time series forecasting work? (2018) — 143 citations
• Forecasting for big data: Does suboptimality matter? (2017) — 48 citations
• The Theta Model: An Essential Forecasting Tool for Supply Chain Planning (2011) — 21 citations
• Forecasting in social settings: The state of the art (2020) — 126 citations
• 'Horses for Courses' in demand forecasting (2014) — 210 citations
• A systemic view of the ADIDA framework (2014) — 30 citations
• Models for optimising the theta method and their relationship to state space models (2016) — 75 citations
• The inventory performance of forecasting methods: Evidence from the M3 competition data (2019) — 58 citations
• Forecasting the novel coronavirus COVID-19 (2020) — 549 citations
• A simple combination of univariate models (2020) — 80 citations
• Forecasting: theory and practice (2020) — 551 citations
• The M4 competition: Bigger. Stronger. Better (2020) — 14 citations
• The M4 competition: Conclusions (2020) — 26 citations
• forecast: Forecasting functions for time series and linear models (2018) — 1,092 citations
• Golden Rule of Forecasting: Be conservative (2015) — 170 citations
• Optimizing Theta Model for Monthly Data (2013) — 13 citations
• A neural network approach for the Theta model (2012) — 6 citations