{"total":18,"rows":[{"id":"2210.13647","title":"Temporally Disentangled Representation Learning","created":"2022-10-24","cited_by_count":61,"area":null},{"id":"2305.10716","title":"A Survey on Time-Series Pre-Trained Models","created":"2023-05-18","cited_by_count":52,"area":null},{"id":"2310.04723","title":"Subspace Identification for Multi-Source Domain Adaptation","created":"2023-10-07","cited_by_count":37,"area":null},{"id":"2405.15325","title":"On the Identification of Temporally Causal Representation with Instantaneous Dependence","created":"2024-05-24","cited_by_count":16,"area":null},{"id":"2503.13868","title":"Out-of-Distribution Generalization in Time Series: A Survey","created":"2025-03-18","cited_by_count":16,"area":null},{"id":"2211.10412","title":"Video Unsupervised Domain Adaptation with Deep Learning: A Comprehensive Survey","created":"2022-11-17","cited_by_count":12,"area":null},{"id":"2311.06554","title":"PGODE: Towards High-quality System Dynamics Modeling","created":"2023-11-11","cited_by_count":7,"area":null},{"id":"2205.03554","title":"Time-Series Domain Adaptation via Sparse Associative Structure Alignment: Learning Invariance and Variance","created":"2022-05-07","cited_by_count":4,"area":null},{"id":"2211.12034","title":"Time Series Forecasting with Hypernetworks Generating Parameters in Advance","created":"2022-11-22","cited_by_count":4,"area":null},{"id":"2404.14073","title":"Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning","created":"2024-04-22","cited_by_count":4,"area":null},{"id":"2306.14114","title":"TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences","created":"2023-06-25","cited_by_count":3,"area":null},{"id":"2503.02836","title":"SeqFusion: Sequential Fusion of Pre-Trained Models for Zero-Shot Time-Series Forecasting","created":"2025-03-04","cited_by_count":3,"area":null},{"id":"2402.12767","title":"Nonstationary Time Series Forecasting via Unknown Distribution Adaptation","created":"2024-02-20","cited_by_count":2,"area":null},{"id":"2407.13194","title":"Robust Multivariate Time Series Forecasting against Intra- and Inter-Series Transitional Shift","created":"2024-07-18","cited_by_count":1,"area":null},{"id":"2502.16637","title":"Time Series Domain Adaptation via Latent Invariant Causal Mechanism","created":"2025-02-23","cited_by_count":1,"area":null},{"id":"2504.00068","title":"Integrating Quantum-Classical Attention in Patch Transformers for Enhanced Time Series Forecasting","created":"2025-03-31","cited_by_count":1,"area":null},{"id":"2401.08221","title":"Towards Causal Relationship in Indefinite Data: Baseline Model and New Datasets","created":"2024-01-16","cited_by_count":0,"area":null},{"id":"2608.30695","title":"Liquid Gated Attention","created":"2026-08-31","cited_by_count":0,"area":null}],"next_cursor":null}