{"total":20,"rows":[{"id":"2408.17253","title":"VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters","created":"2024-08-30","cited_by_count":88,"area":null},{"id":"2205.04216","title":"Forecast combinations: an over 50-year review","created":"2022-05-09","cited_by_count":34,"area":null},{"id":"2502.08869","title":"Harnessing Vision Models for Time Series Analysis: A Survey","created":"2025-02-13","cited_by_count":26,"area":null},{"id":"2503.11835","title":"How Can Time Series Analysis Benefit From Multiple Modalities? A Survey and Outlook","created":"2025-03-14","cited_by_count":20,"area":null},{"id":"2202.01712","title":"Review of automated time series forecasting pipelines","created":"2022-02-03","cited_by_count":18,"area":null},{"id":"2508.04379","title":"VisionTS++: Cross-Modal Time Series Foundation Model with Continual Pre-trained Vision Backbones","created":"2025-08-06","cited_by_count":12,"area":null},{"id":"2403.11047","title":"From Pixels to Predictions: Spectrogram and Vision Transformer for Better Time Series Forecasting","created":"2024-03-17","cited_by_count":9,"area":null},{"id":"2505.24003","title":"Multi-Modal View Enhanced Large Vision Models for Long-Term Time Series Forecasting","created":"2025-05-29","cited_by_count":9,"area":null},{"id":"2505.24030","title":"From Images to Signals: Are Large Vision Models Useful for Time Series Analysis?","created":"2025-05-29","cited_by_count":7,"area":null},{"id":"2506.24124","title":"Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectives","created":"2025-06-30","cited_by_count":7,"area":null},{"id":"2102.12061","title":"Deep Video Prediction for Time Series Forecasting","created":"2021-02-24","cited_by_count":4,"area":null},{"id":"2112.08060","title":"Leveraging Image-based Generative Adversarial Networks for Time Series Generation","created":"2021-12-15","cited_by_count":4,"area":null},{"id":"2103.02941","title":"Exploring the representativeness of the M5 competition data","created":"2021-03-04","cited_by_count":2,"area":null},{"id":"2507.23253","title":"Towards Measuring and Modeling Geometric Structures in Time Series Forecasting via Image Modality","created":"2025-07-31","cited_by_count":2,"area":null},{"id":"2210.14605","title":"Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots","created":"2022-10-26","cited_by_count":1,"area":null},{"id":"2605.12550","title":"SSDA: Bridging Spectral and Structural Gaps via Dual Adaptation for Vision-Based Time Series Forecasting","created":"2026-05-10","cited_by_count":1,"area":null},{"id":"2107.01273","title":"Visual Time Series Forecasting: An Image-driven Approach","created":"2021-07-02","cited_by_count":0,"area":null},{"id":"2206.12882","title":"fETSmcs: Feature-based ETS model component selection","created":"2022-06-26","cited_by_count":0,"area":null},{"id":"2309.13807","title":"Forecasting large collections of time series: feature-based methods","created":"2023-09-25","cited_by_count":0,"area":null},{"id":"2310.20545","title":"Optimizing accuracy and diversity: a multi-task approach to forecast combinations","created":"2023-10-31","cited_by_count":0,"area":null}],"next_cursor":null}