{"total":53,"rows":[{"id":"2405.14616","title":"TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting","created":"2024-05-23","cited_by_count":346,"area":null},{"id":"2410.16032","title":"TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis","created":"2024-10-21","cited_by_count":116,"area":null},{"id":"2409.18479","title":"CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns","created":"2024-09-27","cited_by_count":106,"area":null},{"id":"2305.12095","title":"CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting","created":"2023-05-20","cited_by_count":55,"area":null},{"id":"2308.11200","title":"SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting","created":"2023-08-22","cited_by_count":55,"area":null},{"id":"2404.01340","title":"From Similarity to Superiority: Channel Clustering for Time Series Forecasting","created":"2024-03-31","cited_by_count":37,"area":null},{"id":"2406.03751","title":"Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting","created":"2024-06-06","cited_by_count":34,"area":null},{"id":"2401.13912","title":"A Survey of Deep Learning and Foundation Models for Time Series Forecasting","created":"2024-01-25","cited_by_count":33,"area":null},{"id":"2401.17548","title":"Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators","created":"2024-01-31","cited_by_count":32,"area":null},{"id":"2505.12917","title":"Temporal Query Network for Efficient Multivariate Time Series Forecasting","created":"2025-05-19","cited_by_count":31,"area":null},{"id":"2308.04791","title":"PETformer: Long-term Time Series Forecasting via Placeholder-enhanced Transformer","created":"2023-08-09","cited_by_count":22,"area":null},{"id":"2401.09093","title":"RWKV-TS: Beyond Traditional Recurrent Neural Network for Time Series Tasks","created":"2024-01-17","cited_by_count":22,"area":null},{"id":"2306.02585","title":"MotionTrack: Learning Motion Predictor for Multiple Object Tracking","created":"2023-06-05","cited_by_count":20,"area":null},{"id":"2310.00655","title":"PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting","created":"2023-10-01","cited_by_count":20,"area":null},{"id":"2311.02880","title":"MultiSPANS: A Multi-range Spatial-Temporal Transformer Network for Traffic Forecast via Structural Entropy Optimization","created":"2023-11-06","cited_by_count":13,"area":null},{"id":"2405.03140","title":"TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning","created":"2024-05-06","cited_by_count":12,"area":null},{"id":"2305.10721","title":"Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping","created":"2023-05-18","cited_by_count":11,"area":null},{"id":"2307.01616","title":"SageFormer: Series-Aware Framework for Long-term Multivariate Time Series Forecasting","created":"2023-07-04","cited_by_count":10,"area":null},{"id":"2503.05582","title":"MPTSNet: Integrating Multiscale Periodic Local Patterns and Global Dependencies for Multivariate Time Series Classification","created":"2025-03-07","cited_by_count":10,"area":null},{"id":"2411.02941","title":"A Mamba Foundation Model for Time Series Forecasting","created":"2024-11-05","cited_by_count":9,"area":"ssm"},{"id":"2503.07674","title":"TVNet: A Novel Time Series Analysis Method Based on Dynamic Convolution and 3D-Variation","created":"2025-03-10","cited_by_count":8,"area":null},{"id":"2408.09695","title":"On the Integration of Spatial-Temporal Knowledge: A Lightweight Approach to Atmospheric Time Series Forecasting","created":"2024-08-19","cited_by_count":7,"area":null},{"id":"2305.14649","title":"A Joint Time-frequency Domain Transformer for Multivariate Time Series Forecasting","created":"2023-05-24","cited_by_count":5,"area":null},{"id":"2604.15174","title":"MambaSL: Exploring Single-Layer Mamba for Time Series Classification","created":"2026-04-16","cited_by_count":4,"area":"ssm"},{"id":"2410.17159","title":"LiNo: Advancing Recursive Residual Decomposition of Linear and Nonlinear Patterns for Robust Time Series Forecasting","created":"2024-10-22","cited_by_count":3,"area":null},{"id":"2506.12696","title":"TFKAN: Time-Frequency KAN for Long-Term Time Series Forecasting","created":"2025-06-15","cited_by_count":3,"area":null},{"id":"2401.17802","title":"Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive Learning","created":"2024-01-31","cited_by_count":2,"area":null},{"id":"2311.07744","title":"Two-Stage Aggregation with Dynamic Local Attention for Irregular Time Series","created":"2023-11-13","cited_by_count":1,"area":null},{"id":"2410.01531","title":"TiVaT: A Transformer with a Single Unified Mechanism for Capturing Asynchronous Dependencies in Multivariate Time Series Forecasting","created":"2024-10-02","cited_by_count":1,"area":null},{"id":"2411.04669","title":"EffiCANet: Efficient Time Series Forecasting with Convolutional Attention","created":"2024-11-07","cited_by_count":1,"area":null},{"id":"2411.17770","title":"MTS-UNMixers: Multivariate Time Series Forecasting via Channel-Time Dual Unmixing","created":"2024-11-26","cited_by_count":1,"area":null},{"id":"2412.19423","title":"Revisiting PCA for time series reduction in temporal dimension","created":"2024-12-27","cited_by_count":1,"area":null},{"id":"2503.08328","title":"MFRS: A Multi-Frequency Reference Series Approach to Scalable and Accurate Time-Series Forecasting","created":"2025-03-11","cited_by_count":1,"area":null},{"id":"2509.06060","title":"ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting","created":"2025-09-07","cited_by_count":1,"area":null},{"id":"2511.00989","title":"Hydra: Dual Exponentiated Memory for Multivariate Time Series Analysis","created":"2025-11-02","cited_by_count":1,"area":null},{"id":"2308.10276","title":"Minimalist Traffic Prediction: Linear Layer Is All You Need","created":"2023-08-20","cited_by_count":0,"area":null},{"id":"2308.11204","title":"A Simple Framework for Multi-mode Spatial-Temporal Data Modeling","created":"2023-08-22","cited_by_count":0,"area":null},{"id":"2309.14674","title":"Leveraging Herpangina Data to Enhance Hospital-level Prediction of Hand-Foot-and-Mouth Disease Admissions Using UPTST","created":"2023-09-26","cited_by_count":0,"area":null},{"id":"2310.07323","title":"Multichannel consecutive data cross-extraction with 1DCNN-attention for diagnosis of power transformer","created":"2023-10-11","cited_by_count":0,"area":null},{"id":"2402.18007","title":"Mixer is more than just a model","created":"2024-02-28","cited_by_count":0,"area":null},{"id":"2407.10768","title":"ISMRNN: An Implicitly Segmented RNN Method with Mamba for Long-Term Time Series Forecasting","created":"2024-07-15","cited_by_count":0,"area":"ssm"},{"id":"2412.00772","title":"A Wave is Worth 100 Words: Investigating Cross-Domain Transferability in Time Series","created":"2024-12-01","cited_by_count":0,"area":null},{"id":"2504.14209","title":"Energy-Aware Pattern Disentanglement: A Generalizable Pattern Assisted Architecture for Multi-task Time Series Analysis","created":"2025-04-19","cited_by_count":0,"area":null},{"id":"2505.11017","title":"Logo-LLM: Local and Global Modeling with Large Language Models for Time Series Forecasting","created":"2025-05-16","cited_by_count":0,"area":null},{"id":"2506.17253","title":"MS-DFTVNet:A Long-Term Time Series Prediction Method Based on Multi-Scale Deformable Convolution","created":"2025-06-08","cited_by_count":0,"area":null},{"id":"2506.19567","title":"FAF: A Feature-Adaptive Framework for Few-Shot Time Series Forecasting","created":"2025-06-24","cited_by_count":0,"area":null},{"id":"2510.08661","title":"CATS-Linear: Classification Auxiliary Linear Model for Time Series Forecasting","created":"2025-10-09","cited_by_count":0,"area":null},{"id":"2511.00035","title":"Neural Architecture Search for global multi-step Forecasting of Energy Production Time Series","created":"2025-10-27","cited_by_count":0,"area":null},{"id":"2511.17639","title":"TTF: A Trapezoidal Temporal Fusion Framework for LTV Forecasting in Douyin","created":"2025-11-19","cited_by_count":0,"area":null},{"id":"2511.19497","title":"PeriodNet: Boosting the Potential of Attention Mechanism for Time Series Forecasting","created":"2025-11-23","cited_by_count":0,"area":null},{"id":"2512.14023","title":"Multivariate Time Series Forecasting with Hybrid Euclidean-SPD Manifold Graph Neural Networks","created":"2025-12-16","cited_by_count":0,"area":null},{"id":"2601.01403","title":"A Graph-based Framework for Online Time Series Anomaly Detection Using Model Ensemble","created":"2026-01-04","cited_by_count":0,"area":null},{"id":"2610.13730","title":"SeoulMMOD: A Large-Scale Multimodal Origin-Destination Flow Benchmark","created":"2026-10-09","cited_by_count":0,"area":null}],"next_cursor":null}