Key papers

• DistDF: Time-Series Forecasting Needs Joint-Distribution Wasserstein Alignment (2025)
  Hao Wang et al.
  7.74
• Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends! (2022)
  Luis Gruber and Gregor Kastner
  5.06
• Using binary silver labels in electronic health records-based computable phenotyping algorithms (2026)
  Shuhe Wang et al.
  5.01
• Sampling for Region-Aggregated Spatial Scan Statistics (2026)
  Foad Namjoo et al.
  4.39
• Value-of-Information Analysis for External Validation of Risk Prediction Models in Multicenter Studies and Systematic Reviews (2026)
  Laure Wynants et al.
  4.39
• The Granularity Paradox: How Temporal Disaggregation Inflates In-Sample Fit and Compounds Out-of-Sample Error (2026)
  Hugo Moreira
  4.39
• Learning Temporal Causal Structure via Smooth Differentiable Optimization (2026)
  Tong Zhao et al.
  4.33
• SPDM: Geometry-Modulated State Space Modeling with Manifold Constraints for Time Series Forecasting (2026)
  Xingsheng Chen et al.
  4.33
• Modeling Dynamic Mixtures of Time-Delay Systems from Streaming Time Series (2026)
  Ren Fujiwara et al.
  4.27
• Bounds in Wasserstein Distance for Locally Stationary Functional Time Series (2025)
  Jan Nino G. Tinio et al.
  3.70
• Modeling Time-evolving Causality over Data Streams (2025)
  Naoki Chihara et al.
  3.59
• Wasserstein multivariate auto-regressive models for modeling distributional time series (2022)
  Yiye Jiang et al.
  3.58
• Conformal Inference for Time Series over Graphs (2025)
  Sonakshi Dua et al.
  3.10
• Bayesian Joint Model of Multi-Sensor and Failure Event Data for Multi-Mode Failure Prediction (2025)
  Sina Aghaee Dabaghan Fard et al.
  2.87
• A time warping model for seasonal data with application to age estimation from narwhal tusks (2024)
  Lars N{\o}rtoft Reiter et al.
  2.49
• Nonstationary Time Series Forecasting via Unknown Distribution Adaptation (2024)
  Zijian Li et al.
  2.04
• PAMod: Modeling Cyclical Shifts via Phase-Amplitude Modulation for Non-stationary Time Series Forecasting (2026)
  Yingbo Zhou et al.
  1.89
• Causal Temporal Regime Structure Learning (2023)
  Abdellah Rahmani et al.
  1.87
• Forecasting Multivariate Time Series under Predictive Heterogeneity: A Validation-Driven Clustering Framework (2026)
  Ziling Ma et al.
  1.83
• Aura: Universal Multi-dimensional Exogenous Integration for Aviation Time Series (2026)
  Jiafeng Lin et al.
  1.78
• Enhanced Random Subspace Local Projections for High-Dimensional Time Series Analysis (2026)
  Eman Khalid et al.
  1.78
• Multiple-group (Controlled) Interrupted Time Series Analysis with Higher-Order Autoregressive Errors: A Simulation Study Comparing Newey-West and Prais-Winsten Methods (2026)
  Ariel Linden
  1.78
• Automated univariate time series forecasting with regression trees (2026)
  Francisco Mart\'inez and Mar\'ia P. Fr\'ias
  1.72
• Robust optimal reconciliation for hierarchical time series forecasting with M-estimation (2026)
  Zhichao Wang et al.
  1.72
• Sparse Tucker Decomposition and Graph Regularization for High-Dimensional Time Series Forecasting (2026)
  Sijia Xia et al.
  1.67
• Time-Aware Synthetic Control (2026)
  Saeyoung Rho et al.
  1.67
• An Information-Theoretic Diagnostic Analytics Framework for Mapping Past-Future Dependence in Horizon-Specific Forecastability (2026)
  Peter Maurice Catt
  1.67
• Conformal Prediction Algorithms for Time Series Forecasting: Methods and Benchmarking (2026)
  Andro Sabashvili
  1.67
• On Statistical Inference for High-Dimensional Binary Time Series (2025)
  Dehao Dai et al.
  1.61
• Learning Conditional Independence Differential Graphs From Time-Dependent Data (2025)
  Jitendra K Tugnait
  1.61
• Penalized Estimation and Forecasting of Multiple Subject Intensive Longitudinal Data (2020)
  Zachary F. Fisher and Younghoon Kim and Barbara Fredrickson and Vladas Pipiras
  1.60
• Cross-Population Amplitude Coupling in High-Dimensional Oscillatory Neural Time Series (2021)
  Heejong Bong et al.
  1.60
• Koopman Invariants as Drivers of Emergent Time-Series Clustering in Joint-Embedding Predictive Architectures (2025)
  Pablo Ruiz-Morales et al.
  1.56
• Epistemic Error Decomposition for Multi-step Time Series Forecasting: Rethinking Bias-Variance in Recursive and Direct Strategies (2025)
  Riku Green et al.
  1.56
• A Gentle Introduction to Conformal Time Series Forecasting (2025)
  M. Stocker et al.
  1.56
• Predictive inference for time series: why is split conformal effective despite temporal dependence? (2025)
  Rina Foygel Barber et al.
  1.50
• Noise or Signal? Deconstructing Contradictions and An Adaptive Remedy for Reversible Normalization in Time Series Forecasting (2025)
  Fanzhe Fu et al.
  1.50
• Hierarchical Time Series Forecasting with Robust Reconciliation (2025)
  Shuhei Aikawa et al.
  1.50
• Forecast reconciliation with non-linear constraints (2025)
  Daniele Girolimetto et al.
  1.50
• Select, then Balance: Exploring Exogenous Variable Modeling of Spatio-Temporal Forecasting (2025)
  Wei Chen et al.
  1.44
• Revisiting Multivariate Time Series Forecasting with Missing Values (2025)
  Jie Yang et al.
  1.44
• Online Prediction with Limited Selectivity (2025)
  Licheng Liu and Mingda Qiao
  1.39
• Efficient Causal Discovery for Autoregressive Time Series (2025)
  Mohammad Fesanghary and Achintya Gopal
  1.33
• Preferential subspace identification (PSID) with forward-backward smoothing (2025)
  Omid G. Sani and Maryam M. Shanechi
  1.33
• Rethinking Nonstationarity in Time Series: A Deterministic Trend Perspective (2025)
  Zhandos Abdikhadir et al.
  1.28
• Interpretable Time Series Autoregression for Periodicity Quantification (2025)
  Xinyu Chen et al.
  1.28
• Topology-driven identification of repetitions in multi-variate time series (2025)
  Simon Schindler and Elias Steffen Reich and Saverio Messineo and Simon Hoher and Stefan Huber
  1.22
• Estimation methods of Matrix-valued AR model (2025)
  Kamil Ko{\l}odziejski (Institute of Mathematics et al.
  1.22
• Bayesian Shrinkage in High-Dimensional VAR Models: A Comparative Study (2025)
  Harrison Katz and Robert E. Weiss
  1.17
• Hurdle Network Model With Latent Dynamic Shrinkage For Enhanced Edge Prediction in Zero-Inflated Directed Network Time Series (2025)
  Sandipan Pramanik et al.
  1.17
• Generalized network autoregressive modelling of longitudinal networks with application to presidential elections in the USA (2025)
  Guy Nason et al.
  1.11
• Surrogate Modeling for Explainable Predictive Time Series Corrections (2024)
  Alfredo Lopez et al.
  1.00
• Investigating the performance of the Phase II Hotelling T2 chart when monitoring multivariate time series observations (2025)
  Adel Ahmadi Nadi et al.
  1.00
• Ridge Regression on Riemannian Manifolds for Time-Series Prediction (2024)
  Esfandiar Nava-Yazdani
  0.94
• Identification and estimation for matrix time series CP-factor models (2024)
  Jinyuan Chang et al.
  0.89
• Simultaneous Graphical Dynamic Modeling (2024)
  Mike West and Luke Vrotsos
  0.89
• Bayesian Projection of Extant Refugee and Asylum Seeker Populations (2024)
  Herbert Susmann et al.
  0.61
• An Adaptive Learning Approach to Multivariate Time Forecasting in Industrial Processes (2024)
  Fernando Miguelez et al.
  0.50
• Multiple Imputation of Hierarchical Nonlinear Time Series Data with an Application to School Enrollment Data (2024)
  Daphne H. Liu and Adrian E. Raftery
  0.39
• Selecting time-series hyperparameters with the artificial jackknife (2020)
  Filippo Pellegrino
  0.00