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  1. Measuring the Advantages of Contemporaneous Aggregation in Forecasting. by Li, Zeda, and William W. S. Wei, Journal of Forecasting (2024). [DOI]
  2. NeuralReconciler for Hierarchical Time Series Forecasting. by Wang, Shiyu, In Proceedings of the 17th ACM International Conference on Web Search and Data Mining (2024). [DOI]
  3. Smooth Forecast Reconciliation. by Ando, Sakai, IMF Working Papers (2024).
  4. GMP-AR: Granularity Message Passing and Adaptive Reconciliation for Temporal Hierarchy Forecasting. by Zhou, Fan, Chen Pan, Lintao Ma, Yu Liu, Siqiao Xue, James Zhang, Jun Zhou, et al, In Proceedings of the 38th AAAI Conference on Artificial Intelligence (2024). [DOI]
  5. Constructing Hierarchical Time Series through Clustering: Is There an Optimal Way for Forecasting? by Zhang, Bohan, Anastasios Panagiotelis, and Han Li (2024). [arXiv]
  6. Probabilistic Reconciliation of Mixed-Type Hierarchical Time Series. by Zambon, Lorenzo, Dario Azzimonti, Nicolò Rubattu, and Giorgio Corani, In The 40th Conference on Uncertainty in Artificial Intelligence (2024). [URL]
  7. Improving Crime Count Forecasts in the City of Rio de Janeiro via Reconciliation. by Nascimento, Marcus L., and Leonardo M. Barreto, Security Journal (2024). [DOI]
  8. Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series. by Tsiourvas, Asterios, Wei Sun, Georgia Perakis, Pin-Yu Chen, and Yada Zhu, In Forty-First International Conference on Machine Learning (2024). [URL]
  9. Large Scale Hierarchical Industrial Demand Time-Series Forecasting Incorporating Sparsity. by Kamarthi, Harshavardhan, Aditya B. Sasanur, Xinjie Tong, Xingyu Zhou, James Peters, Joe Czyzyk, and B. Aditya Prakash (2024). [arXiv]
  10. Forecasting the Waste Production Hierarchical Time Series with Correlation Structure. by Eryganov, Ivan, Martin Rosecký, Radovan Šomplák, and Veronika Smejkalová, Optimization and Engineering (2024). [DOI]
  11. Hourly Forecasting of Emergency Department Arrivals for Different ESI Levels. by Mashinkarjavan, Shaghayegh (2024). [URL]
  12. Forecasting Mail Flow: A Hierarchical Approach for Enhanced Societal Wellbeing. by Kafa, Nadine, M. Zied Babai, and Walid Klibi, International Journal of Forecasting (2024). [DOI]
  13. Efficient and Accurate Forecasting in Large-Scale Settings. by Sprangers, Olivier R, University of Amsterdam (2024). [URL]
  14. Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning. by Rombouts, Jeroen, Marie Ternes, and Ines Wilms, International Journal of Forecasting (2024). [DOI]
  15. Properties of the Reconciled Distributions for Gaussian and Count Forecasts. by Zambon, Lorenzo, Arianna Agosto, Paolo Giudici, and Giorgio Corani, International Journal of Forecasting (2024) [DOI]

Incomplete information

  1. Coherent forecasts for tourism demand with automated immutability constraints by Q Wen, Y Zeng, F Petropoulos, Y Kang, Tourism Management (2026).
  2. Hierarchical Time Series Forecasting with Robust Reconciliation by S Aikawa, A Suzuki, K Yoshitake, K Teshigawara… (2025). [arXiv]
  3. Improving load forecasts in Italian bidding zones: A coherent combination approach by D Girolimetto (2025).
  4. Non-Negative Forecast Reconciliation: Optimal Methods and Operational Solutions by D Girolimetto, Forecasting (2025).
  5. Forecast reconciliation with non-linear constraints by D Girolimetto, A Panagiotelis, T Di Fonzo, H Li (2025). [arXiv]
  6. Forecasting for Empty Container Repositioning. by M Zugno, L Petersen, W Ponikiewski…, Foresight: The International … (2025).
  7. Forecasting intraday particle number size distribution: A functional time series approach by HL Shang, IM Hernandez (2025). [arXiv]
  8. Integrating AI and Ensemble Forecasting: Explainable Materials Planning with Scorecards and Trend Insights for a Large-Scale Manufacturer by S Venkatachalam (2025). [arXiv]
  9. Heuristic Cross-Temporal Reconciliation Applied to Heterogeneous Models in Photovoltaic Forecasting by FC Gonzaleza, A Gudiño, FC Gonzaleza, A Gudiño-Ochoaa.
  10. The Influence of Foreign and Domestic Investment on Regional GDP Growth: A Panel Data Analysis by SW Soegoto, S Natsir, HW Adda, RP Adam, Jurnal Ilmiah Akuntansi Kesatuan (2025).
  11. Improving wind power forecasting accuracy through bias correction of wind speed predictions by E Spiliotis, E Theodorou, Sustainable Energy Technologies and Assessments (2025).
  12. A Study on Enhancing Hierarchical Time Series Forecasting employing Machine Learning Models by RC Mahalik, S Panigrahi, RC Mahalik, S Panigrahi - 2024 (2024).
  13. Hierarchical Forecasting of Italian Mortality Data with Gender and Cause of Death Reconciliation by GL Baldi, R Mattera, A Nigri, H Shang, ITALIAN STATISTICAL SOCIETY SERIES … (2025).
  14. A Novel Shrinkage Estimator of the Covariance Matrix for Hierarchical Time Series by C Carrara, L Zambon, D Azzimonti, G Corani, … Meeting of the Italian Statistical Society (2025).
  15. Hierarchical Forecasting of Italian by H Shang, Statistics for Innovation III: SIS 2025, Short Papers … (2025).
  16. HiGN-ARec: A Hierarchical Graph Network with Adaptive Reconciliation for PV Power Forecasting in Spatial Hierarchy by Y Yang, P Wang, S Shu, F Lin, IEEE Transactions on Sustainable Energy (2025).
  17. Modeling the uncertainty on the covariance matrix for probabilistic forecast reconciliation by C Carrara, L Zambon, D Azzimonti, G Corani (2025). [arXiv]
  18. Joint Bottom-up Method for Probabilistic Forecasting of Hierarchical Time Series by N Bertani, ST Jensen, VA Satopää, Operations Research (2025).
  19. Coherent forecast combination for linearly constrained multiple time series by D Girolimetto, T Di Fonzo (2024). [arXiv]
  20. Ensemble-Based Hierarchical Modelling for Forecasting Traffic Accident Victims by M Silfiani, NP Lustyadi, M Silfiani, NP Lustyadi.
  21. A Python Package to Assist Macroframework Forecasting by S Ando, S Das, S Orazbayev, S Ando, S Das, S Orazbayev - 2025 (2025).
  22. Recurrent neural networks for hierarchical time series forecasting: An application to the S&P 500 market value by JN Munyao, LA Oluoch, H Iftikhar, PC Rodrigues, JN Munyao, LA Oluoch, H Iftikhar, PC Rodrigues - Physica A: Statistical Mechanics …, 202 (202).
  23. Stealing Accuracy: Predicting Day-ahead Electricity Prices with Temporal Hierarchy Forecasting (THieF) by A Lipiecki, K Bilinska, N Kourentzes, R Weron (2025). [arXiv]
  24. MFFDM-WLS: A multi-granularity feature-based coherent forecasting method for temporal hierarchical wind speed time series by Y Wang, X Duan, F Zhang, G Wu, R Zou, J Wan, Q Hu, Applied Energy (2025).
  25. FRT: Flow-based Reconcile Transformer for Hierarchical Time Series by S Wang, W Lu, J Li, X Shi, X Zhong, Z Ye, M Jin, Q Wen, Proceedings of the 31st … (2025).
  26. Geometry of nonlinear forecast reconciliation by L Nespoli, A Biswas, V Medici (2025). [arXiv]
  27. BayesReconPy: A Python package for forecast reconciliation by A Biswas, L Nespoli, D Azzimonti, L Zambon…, Journal of Open Source … (2025).
  28. The power of information sharing: evaluating POS and order data for hierarchical forecasting in multi-echelon supply chains by M Abolghasemi, International Journal of Production Research (2025).
  29. Memory Augmented Coherent Probabilistic Forecasts for Hierarchically Related Time Series by J Lee, Y Byun, B Koo, JG Baek, Neurocomputing (2025).
  30. Short-term CO2 emissions forecasting: insight from the Italian electricity market by P Duttilo, F Lisi (2025). [arXiv]
  31. Riconciliazione di previsioni per serie storiche intermittenti by JR NAPOLI, JR NAPOLI.
  32. Comparative Analysis of Machine Learning and Deep Learning Models for Tourism Demand Forecasting with Economic Indicators by I Vasenska, I Vasenska - 2025 (2025).
  33. Hierarchical deep learning for consistent multi‐timescale hydrological forecasting by MS Jahangir, J Quilty, Water Resources Research (2025).
  34. Deep Learning Applications in Hierarchical Time Series Forecasting of Market Value by JK Mutinda, L Yong, Computational Economics (2025).
  35. Long-Term Multi-Resolution Probabilistic Load Forecasting Using Temporal Hierarchies by S Bahman, H Zareipour, Energies (2025).
  36. Linear vs. Machine Learning Approaches for Cross-Temporal Forecast Reconciliation with an Application to Italian Energy Load Data by L Bisaglia, R Ghamari, D Girolimetto, Scientific Meeting of the Italian Statistical … (2025).
  37. Forecast reconciliation and Multivariate GARCH by M Caporin, D Girolimetto, E Lopetuso, M Caporin, D Girolimetto, E Lopetuso - BOOK OF SHORT PAPERS.
  38. Comparative Analysis of Reconciliation Techniques: Bottom-Up, Top-Down, and MinT for Product Forecasting in Retail SMEs by D Rambing, R Kusumaningrum, A Sugiharto, D Rambing, R Kusumaningrum, A Sugiharto - ComTech: Computer, Mathematics and …,.
  39. Improving cross-temporal forecasts reconciliation accuracy and utility in energy market by M Abolghasemi, D Girolimetto, T Di Fonzo, Applied Energy (2025).
  40. INFERRING DAILY GAS CONSUMPTION FROM MULTIPLE NONUNIFORMLY SAMPLED BILLING CYCLES WITH HIERARCHICAL CONSTRAINTS by CO Quinn, CO Quinn - 2025 (2025).
  41. Linear and machine learning cross-temporal forecast reconciliation: An empirical investigation by R GHAMARI, R GHAMARI.
  42. Deep Hierarchical Learning for 3D Semantic Segmentation by C Li, Y Liu, X Li, Y Zhang, T Li, J Yuan, International Journal of Computer Vision (2025).
  43. CoRe: Coherency Regularization for Hierarchical Time Series by R Cristian, P Harhsa, G Perakis, B Quanz (2025). [arXiv]
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  45. Forecasting Italian daily electricity generation disaggregated by geographical zones and energy sources using coherent forecast combination by D Girolimetto, T Di Fonzo (2025). [arXiv]
  46. Energy load forecasting using Terna public data: a free lunch multi-task combination approach by D Girolimetto, T Di Fonzo (2025). [arXiv]
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  48. Enhanced Renewable Energy Forecasting and Operations through Probabilistic Forecast Aggregation by A Moradi, M Tanneau, R Zandehshahvar… (2025). [[arXiv](http://arxiv.org/abs/arXiv preprint arXiv …)]
  49. Value-oriented forecast reconciliation for renewables in electricity markets by H Wen, P Pinson (2025). [arXiv]
  50. HIERARCHICAL FORECASTING OF CAuSES OF DEATH WITH TREND BREAKS IN MORTALITY MODELING: KENYAN CASE by N Bett, J Kasozi, D Ruturwa, N Bett, J Kasozi, D Ruturwa - 2025 (2025).
  51. A novel sales forecast framework based on separate feature extraction and reconciliation under hierarchical constraint by X Yan, H Zhang, Q Miao, Computers & Industrial Engineering (2025).
  52. Spatio-temporal clustering and reconciliation for regional electricity demand forecasting by M Brégère, R Mattera, M Brégère, R Mattera - 2025 (2025).
  53. A Comprehensive Forecasting Framework based on Multi-Stage Hierarchical Forecasting Reconciliation and Adjustment by Z Yang, M Ghosh, A Saha, D Xu, K Shmakov, K Lee (2024). [arXiv]
  54. Balancing Accuracy and Costs in Cross-Temporal Hierarchies: Investigating Decision-Based and Validation-Based Reconciliation by M Abolghasemi, D Girolimetto, T Di Fonzo (2024). [arXiv]
  55. Comparison Between Hierarchical Time Series Forecasting Approaches for the Electricity Consumption in the Brazilian Industrial Sector by M Mesquita Lopes Cabreira, F Leite Coelho da Silva…, Applied Stochastic Models … (2024).
  56. Hierarchical Spatio-Temporal Uncertainty Quantification for Distributed Energy Adoption by W Zhou, S Zhu, F Qiu, X Wu (2024). [arXiv]
  57. Enhancing Hierarchical Sales Forecasting with Promotional Data: A Comparative Study Using ARIMA and Deep Neural Networks by M Teixeira, JM Oliveira, P Ramos, Machine Learning and Knowledge Extraction (2024).
  58. Local vs. Global Models for Hierarchical Forecasting by Z Yingjie, M Abolghasemi (2024). [arXiv]
  59. Enhancing Forecasts Using Real-Time Data Flow and Hierarchical Forecast Reconciliation, with Applications to the Energy Sector by L Neubauer, P Filzmoser (2024). [arXiv]
  60. A Study on Enhancing Hierarchical Time Series Forecasting employing Machine Learning Models by RC Mahalik, S Panigrahi, RC Mahalik, S Panigrahi - 2024 (2024).
  61. FNNGM: A neural-driven fractional-derivative multivariate fusion model for interpretable real-time CPI forecasts by S Ding, Z Cai, Y Wu, H Zhang, X Shen, Based Systems (2024).
  62. Iterative Trace Minimization for the Reconciliation of Very Short Hierarchical Time Series by L Steinmeister, M Pauly (2024). [arXiv]
  63. HierNBeats: Hierarchical Neural Basis Expansion Analysis for Hierarchical Time Series Forecasting by H Sun, W Tu, J Zhan, W Zhao, International Conference on Artificial Neural Networks (2024).
  64. Scaleable Dynamic Forecast Reconciliation by R Hollyman, F Petropoulos, ME Tipping (2024). [arXiv]