{"total":41,"rows":[{"id":"2105.02675","title":"Granger Causality: A Review and Recent Advances","created":"2021-05-05","cited_by_count":63,"area":null},{"id":"2212.03523","title":"Criteria for Classifying Forecasting Methods","created":"2022-12-07","cited_by_count":48,"area":null},{"id":"2103.05896","title":"Streaming Linear System Identification with Reverse Experience Replay","created":"2021-03-10","cited_by_count":17,"area":null},{"id":"2207.13554","title":"Data-Driven Sample Average Approximation with Covariate Information","created":"2022-07-27","cited_by_count":14,"area":null},{"id":"2202.13157","title":"High Dimensional Statistical Estimation under Uniformly Dithered One-bit Quantization","created":"2022-02-26","cited_by_count":13,"area":null},{"id":"2111.09831","title":"Causal Forecasting:Generalization Bounds for Autoregressive Models","created":"2021-11-18","cited_by_count":5,"area":null},{"id":"2203.10651","title":"Forecasting Sparse Movement Speed of Urban Road Networks with Nonstationary Temporal Matrix Factorization","created":"2022-03-20","cited_by_count":5,"area":null},{"id":"2303.15121","title":"Learning linear dynamical systems under convex constraints","created":"2023-03-27","cited_by_count":5,"area":null},{"id":"2110.00852","title":"Efficient and passive learning of networked dynamical systems driven by non-white exogenous inputs","created":"2021-10-02","cited_by_count":4,"area":null},{"id":"2204.08369","title":"Benign Overfitting in Time Series Linear Models with Over-Parameterization","created":"2022-04-18","cited_by_count":4,"area":null},{"id":"2409.01362","title":"Correlating Time Series with Interpretable Convolutional Kernels","created":"2024-09-02","cited_by_count":3,"area":null},{"id":"2208.03703","title":"Granger Causality using Neural Networks","created":"2022-08-07","cited_by_count":2,"area":null},{"id":"2308.16859","title":"Information Theoretically Optimal Sample Complexity of Learning Dynamical Directed Acyclic Graphs","created":"2023-08-31","cited_by_count":2,"area":null},{"id":"2404.19073","title":"Learning Sparse High-Dimensional Matrix-Valued Graphical Models From Dependent Data","created":"2024-04-29","cited_by_count":2,"area":null},{"id":"2501.15388","title":"Guaranteed Multidimensional Time Series Prediction via Deterministic Tensor Completion Theory","created":"2025-01-26","cited_by_count":2,"area":null},{"id":"2507.03310","title":"Causal Discovery for Irregularly Time Series with Consistency Guarantees","created":"2025-07-04","cited_by_count":2,"area":null},{"id":"2109.10947","title":"Causal Discovery in High-Dimensional Point Process Networks with Hidden Nodes","created":"2021-09-22","cited_by_count":1,"area":null},{"id":"2109.11634","title":"Joint Estimation and Inference for Multi-Experiment Networks of High-Dimensional Point Processes","created":"2021-09-23","cited_by_count":1,"area":null},{"id":"2112.12909","title":"Optimal Variable Clustering for High-Dimensional Matrix Valued Data","created":"2021-12-24","cited_by_count":1,"area":null},{"id":"2205.00007","title":"Graph Learning from Multivariate Dependent Time Series via a Multi-Attribute Formulation","created":"2022-04-29","cited_by_count":1,"area":null},{"id":"2307.12395","title":"Concentration inequalities for high-dimensional linear processes with dependent innovations","created":"2023-07-23","cited_by_count":1,"area":null},{"id":"2102.09232","title":"The Variational Bayesian Inference for Network Autoregression Models","created":"2021-02-18","cited_by_count":0,"area":null},{"id":"2106.09327","title":"Minimax Estimation of Partially-Observed Vector AutoRegressions","created":"2021-06-17","cited_by_count":0,"area":null},{"id":"2206.03329","title":"Concentration analysis of multivariate elliptic diffusion processes","created":"2022-06-07","cited_by_count":0,"area":null},{"id":"2209.01172","title":"An Interpretable and Efficient Infinite-Order Vector Autoregressive Model for High-Dimensional Time Series","created":"2022-09-02","cited_by_count":0,"area":null},{"id":"2210.07456","title":"Estimation of High-Dimensional Markov-Switching VAR Models with an Approximate EM Algorithm","created":"2022-10-14","cited_by_count":0,"area":null},{"id":"2212.12845","title":"Mining the Factor Zoo: Estimation of Latent Factor Models with Sufficient Proxies","created":"2022-12-25","cited_by_count":0,"area":null},{"id":"2303.02114","title":"Lag selection and estimation of stable parameters for multiple autoregressive processes through convex programming","created":"2023-03-03","cited_by_count":0,"area":null},{"id":"2311.08658","title":"Structured Estimation of Heterogeneous Time Series","created":"2023-11-15","cited_by_count":0,"area":null},{"id":"2402.16131","title":"A VAE-based Framework for Learning Multi-Level Neural Granger-Causal Connectivity","created":"2024-02-25","cited_by_count":0,"area":null},{"id":"2405.10719","title":"$\\ell_1$-Regularized Generalized Least Squares","created":"2024-05-17","cited_by_count":0,"area":null},{"id":"2412.03768","title":"Learning Networks from Wide-Sense Stationary Stochastic Processes","created":"2024-12-04","cited_by_count":0,"area":null},{"id":"2502.02109","title":"Causally-informed Deep Learning towards Explainable and Generalizable Outcomes Prediction in Critical Care","created":"2025-02-04","cited_by_count":0,"area":null},{"id":"2503.08579","title":"Sparsity-Induced Global Matrix Autoregressive Model with Auxiliary Network Data","created":"2025-03-11","cited_by_count":0,"area":null},{"id":"2504.15691","title":"Transfer Learning for High-dimensional Reduced Rank Time Series Models","created":"2025-04-22","cited_by_count":0,"area":null},{"id":"2511.06189","title":"Counterfactual Forecasting for Panel Data","created":"2025-11-09","cited_by_count":0,"area":null},{"id":"2512.07557","title":"On Conditional Independence Graph Learning From Multi-Attribute Gaussian Dependent Time Series","created":"2025-12-08","cited_by_count":0,"area":null},{"id":"2602.11533","title":"AltTS: A Dual-Path Framework with Alternating Optimization for Multivariate Time Series Forecasting","created":"2026-02-12","cited_by_count":0,"area":null},{"id":"2605.09075","title":"Optimality of Sub-network Laplace Approximations: New Results and Methods","created":"2026-05-09","cited_by_count":0,"area":null},{"id":"2609.25326","title":"Spatiotemporal Kronecker Covariance Neural Networks","created":"2026-09-21","cited_by_count":0,"area":null},{"id":"2610.05618","title":"Causal Lag Structure Discovery in Confounded Time Series via Orthogonalized Adaptive Estimation","created":"2026-10-04","cited_by_count":0,"area":null}],"next_cursor":null}