List of research papers focus on time series forecasting and deep learning, as well as other resources like competitions, datasets, courses, blogs, code, etc.
This collection primarily focuses on time series forecasting. It also covers adjacent time series tasks, including anomaly detection, classification, imputation, generation, and representation learning.
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Channel Adapter for Time Series Foundation Models in Zero-Shot Multivariate Forecasting
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DualTimesField: Rethinking Time Series as Continuous-Time Trends and Events
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Falcon-X: A Time Series Foundation Model for Heterogeneous Multivariate Modeling
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Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting
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SeesawNet: Towards Non-stationary Time Series Forecasting with Balanced Modeling of Common and Specific Dependencies
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Characteristic Root Analysis and Regularization for Linear Time Series Forecasting
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EventTSF: Event-Aware Non-Stationary Time Series Forecasting
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TEDM: Time Series Forecasting with Elucidated Diffusion Models
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Re-Diffusion: Modeling Latent Residuals with Diffusion for Time-Series Forecasting
- 12 Apr 2026, Boning Zhang, et al.
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AlphaCast: A Human Wisdom-LLM Intelligence Co-Reasoning Framework for Interactive Time Series Forecasting
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TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectiveness
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CoRA: Boosting Time Series Foundation Models for Multivariate Forecasting through Correlation-aware Adapter
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Time Tracker: Mixture-of-Experts-Enhanced Foundation Time Series Forecasting Model with Decoupled Training Pipelines
- 18 Mar 2026, Aobo Liang, et al.
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Unlocking the Value of Text: Event-Driven Reasoning and Multi-Level Alignment for Time Series Forecasting
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TimeCAP: A Channel-Aware Pre-Training Framework for Multivariate Time Series Forecasting
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From Tokenizer Bias to Backbone Capability: A Controlled Study of LLMs for Time Series Forecasting
- 06 Mar 2026, Xinyu Zhang, et al.
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Position: Beyond Model-Centric Prediction – Agentic Time Series Forecasting
- 05 Mar 2026, Mingyue Cheng, et al.
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Adapt Data to Model: Adaptive Transformation Optimization for Domain-shared Time Series Foundation Models
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CPiRi: Channel Permutation-Invariant Relational Interaction for Multivariate Time Series Forecasting
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Learning Recursive Multi-Scale Representations for Irregular Multivariate Time Series Forecasting
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SciTS: Scientific Time Series Understanding and Generation with LLMs
- 25 Feb 2026, Wen Wu, et al.
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TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts
- 25 Feb 2026, Jiafeng Lin, et al.
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TimeOmni-1: Incentivizing Complex Reasoning with Time Series in Large Language Models
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SEMixer: Semantics Enhanced MLP-Mixer for Multiscale Mixing and Long-term Time Series Forecasting
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MixLinear: Extreme Low Resource Multivariate Time Series Forecasting with 0.1K Parameters
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Test-Time Efficient Pretrained Model Portfolios for Time Series Forecasting
- 11 Feb 2026, Mert Kayaalp, et al.
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StretchTime: Adaptive Time Series Forecasting via Symplectic Attention
- 09 Feb 2026, Yubin Kim, et al.
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Position: The Inevitable End of One-Architecture-Fits-All-Domains in Time Series Forecasting
- 02 Feb 2026, Qinwei Ma, et al.
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Conformal Prediction Algorithms for Time Series Forecasting: Methods and Benchmarking
- 30 Jan 2026, Andro Sabashvili, et al.
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A Comprehensive Survey of Deep Learning for Multivariate Time Series Forecasting: A Channel Strategy Perspective
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Beyond Accuracy: Are Time Series Foundation Models Well-Calibrated?
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Time series forecasting with Hahn Kolmogorov-Arnold networks
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ReCast: Reliability-aware Codebook Assisted Lightweight Time Series Forecasting
- 09 Jan 2026, Xiang Ma, et al.
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TimeDistill: Efficient Long-Term Time Series Forecasting with MLP via Cross-Architecture Distillation
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Dynamic Sector Fusion Transformer for Stock Index Prediction
- 16 Dec 2025, Xu Wang, et al.
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FusAD: Time-Frequency Fusion with Adaptive Denoising for General Time Series Analysis
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TwinFormer: A Dual-Level Transformer for Long-Sequence Time-Series Forecasting
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Sonnet: Spectral Operator Neural Network for Multivariable Time Series Forecasting
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Time Series Forecasting via Direct Per-Step Probability Distribution Modeling
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RI-Loss: A Learnable Residual-Informed Loss for Time Series Forecasting
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SimDiff: Simpler Yet Better Diffusion Model for Time Series Point Forecasting
- 24 Nov 2025, Hang Ding, et al.
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Adapformer: Adaptive Channel Management for Multivariate Time Series Forecasting
- 18 Nov 2025, Yuchen Luo, et al.
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Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline
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OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting
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Beyond MSE: Ordinal Cross-Entropy for Probabilistic Time Series Forecasting
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MDMLP-EIA: Multi-domain Dynamic MLPs with Energy Invariant Attention for Time Series Forecasting
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CaReTS: A Multi-Task Framework Unifying Classification and Regression for Time Series Forecasting
- 12 Nov 2025, Fulong Yao, et al.
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EMAformer: Enhancing Transformer through Embedding Armor for Time Series Forecasting
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LEAF: Large Language Diffusion Model for Time Series Forecasting
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This Time is Different: An Observability Perspective on Time Series Foundation Models
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SST: Multi-Scale Hybrid Mamba-Transformer Experts for Time Series Forecasting
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Multi-Modal View Enhanced Large Vision Models for Long-Term Time Series Forecasting
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TempoPFN: Synthetic Pre-training of Linear RNNs for Zero-shot Time Series Forecasting
- 31 Oct 2025, Vladyslav Moroshan, et al.
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Selective Learning for Deep Time Series Forecasting
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Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models
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Not All Data are Good Labels: On the Self-supervised Labeling for Time Series Forecasting
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SwiftTS: A Swift Selection Framework for Time Series Pre-trained Models via Multi-task Meta-Learning
- 27 Oct 2025, Tengxue Zhang, et al.
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DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting
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Abstain Mask Retain Core: Time Series Prediction by Adaptive Masking Loss with Representation Consistency
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SEMPO: Lightweight Foundation Models for Time Series Forecasting
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Understanding the Implicit Biases of Design Choices for Time Series Foundation Models
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Enhancing Time Series Forecasting through Selective Representation Spaces: A Patch Perspective
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Chronos-2: From Univariate to Universal Forecasting
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Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift
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Time Series Foundation Models: Benchmarking Challenges and Requirements
- 15 Oct 2025, Marcel Meyer, et al.
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Multi-Scale Finetuning for Encoder-based Time Series Foundation Models
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Benchmarking M-LTSF: Frequency and Noise-Based Evaluation of Multivariate Long Time Series Forecasting Models
- 06 Oct 2025, Nick Janßen, et al.
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PhaseFormer: From Patches to Phases for Efficient and Effective Time Series Forecasting
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Understanding Transformers for Time Series: Rank Structure, Flow-of-ranks, and Compressibility
- 02 Oct 2025, Annan Yu, et al.
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U-Cast: Learning Hierarchical Structures for High-Dimensional Time Series Forecasting
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Why Attention Fails: The Degeneration of Transformers into MLPs in Time Series Forecasting
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DPANet: Dual Pyramid Attention Network for Multivariate Time Series Forecasting
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DAG: A Dual Causal Network for Time Series Forecasting with Exogenous Variables
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Super-Linear: A Lightweight Pretrained Mixture of Linear Experts for Time Series Forecasting
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Text Reinforcement for Multimodal Time Series Forecasting
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FinCast: A Foundation Model for Financial Time-Series Forecasting
- 27 Aug 2025, Zhuohang Zhu, et al.
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FLAIRR-TS – Forecasting LLM-Agents with Iterative Refinement and Retrieval for Time Series
- 24 Aug 2025, Gunjan Jalori, et al.
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Interpreting Time Series Forecasts with LIME and SHAP: A Case Study on the Air Passengers Dataset
- 17 Aug 2025, Manish Shukla, et al.
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Wavelet Mixture of Experts for Time Series Forecasting
- 12 Aug 2025, Zheng Zhou, et al.
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From Values to Tokens: An LLM-Driven Framework for Context-aware Time Series Forecasting via Symbolic Discretization
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T3Time: Tri-Modal Time Series Forecasting via Adaptive Multi-Head Alignment and Residual Fusion
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CMA: A Unified Contextual Meta-Adaptation Methodology for Time-Series Denoising and Prediction
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Enhancer: A Distribution-Aware Framework with Temporal-Relational Meta-Learning for Stock Prediction
- 03 Aug 2025, Weijun Chen, et al.
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Tailored Forecasting from Short Time Series via Meta-learning
- 31 Jul 2025, Declan A. Norton, et al.
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Multi-period Learning for Financial Time Series Forecasting
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FLDmamba: Integrating Fourier and Laplace Transform Decomposition with Mamba for Enhanced Time Series Prediction
- 17 Jul 2025, Qianru Zhang, et al.
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The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting
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Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting
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TimeBase: The Power of Minimalism in Efficient Long-term Time Series Forecasting
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MoFE-Time: Mixture of Frequency Domain Experts for Time-Series Forecasting Models
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Non-collective Calibrating Strategy for Time Series Forecasting
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LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization
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The language of time: a language model perspective on time-series foundation models
- 29 Jun 2025, Yi Xie, et al.
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Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs
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TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting
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Mamba time series forecasting with uncertainty quantification
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Can Slow-thinking LLMs Reason Over Time? Empirical Studies in Time Series Forecasting
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Explore the Time Series Forecasting Potential of TabPFN Leveraging the Intrinsic Periodicity of Data
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KARMA: A Multilevel Decomposition Hybrid Mamba Framework for Multivariate Long-Term Time Series Forecasting
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LightGTS: A Lightweight General Time Series Forecasting Model
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Timing is Important: Risk-aware Fund Allocation based on Time-Series Forecasting
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Winner-takes-all for Multivariate Probabilistic Time Series Forecasting
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Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal Narrative
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IMTS is Worth Time × Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction
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K2 VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting
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Sundial: A Family of Highly Capable Time Series Foundation Models
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Improving Time Series Forecasting via Instance-aware Post-hoc Revision
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Less is More: Unlocking Specialization of Time Series Foundation Models via Structured Pruning
- 29 May 2025, Lifan Zhao, et al.
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Explainable Multi-modal Time Series Prediction with LLM-in-the-Loop
- 27 May 2025, Yushan Jiang, et al.
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TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state
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CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial Correlations
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HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting
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ReAugment: Model Zoo-Guided RL for Few-Shot Time Series Augmentation and Forecasting
- 22 May 2025, Haochen Yuan, et al.
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Output Scaling: YingLong-Delayed Chain of Thought in a Large Pretrained Time Series Forecasting Model
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TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting
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Non-stationary Diffusion For Probabilistic Time Series Forecasting
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Temporal Query Network for Efficient Multivariate Time Series Forecasting
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Intervention-Aware Forecasting: Breaking Historical Limits from a System Perspective
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OLinear: A Linear Model for Time Series Forecasting in Orthogonally Transformed Domain
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DELPHYNE: A Pre-Trained Model for General and Financial Time Series
- 12 May 2025, Xueying Ding, et al.
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FilterTS: Comprehensive Frequency Filtering for Multivariate Time Series Forecasting
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Retrieval Augmented Time Series Forecasting
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Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation
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FreDF: Learning to Forecast in the Frequency Domain
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CASA: CNN Autoencoder-based Score Attention for Efficient Multivariate Long-term Time-series Forecasting
- 04 May 2025, Minhyuk Lee, et al.
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A Closer Look at Transformers for Time Series Forecasting: Understanding Why They Work and Where They Struggle
- 01 May 2025, Yu Chen, et al.
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Hi-Patch: Hierarchical Patch GNN for Irregular Multivariate Time Series
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ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoning
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A Comprehensive Survey of Time Series Forecasting: Concepts, Challenges, and Future Directions
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ms-Mamba: Multi-scale Mamba for Time-Series Forecasting
- 10 Apr 2025, Yusuf Meric Karadag, et al.
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Foundation Models for Time Series: A Survey
- 05 Apr 2025, Siva Rama Krishna Kottapalli, et al.
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Integrating Quantum-Classical Attention in Patch Transformers for Enhanced Time Series Forecasting
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TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment
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BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Models
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TSKANMixer: Kolmogorov-Arnold Networks with MLP-Mixer Model for Time Series Forecasting
- 27 Mar 2025, Young-Chae Hong, et al.
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Towards Neural Scaling Laws for Time Series Foundation Models
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FreqMoE: Enhancing Time Series Forecasting through Frequency Decomposition Mixture of Experts
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ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables
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Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting
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Minimal Time Series Transformer
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TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents
- 10 Mar 2025, Geon Lee, et al.
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TS-LIF: A Temporal Segment Spiking Neuron Network for Time Series Forecasting
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TimeFound: A Foundation Model for Time Series Forecasting
- 06 Mar 2025, Congxi Xiao, et al.
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Patch-wise Structural Loss for Time Series Forecasting
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TimesBERT: A BERT-Style Foundation Model for Time Series Understanding
- 28 Feb 2025, Haoran Zhang, et al
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Efficient Time Series Forecasting via Hyper-Complex Models and Frequency Aggregation
- 27 Feb 2025, Eyal Yakir, et al.
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TimeKAN: KAN-based Frequency Decomposition Learning Architecture for Long-term Time Series Forecasting
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Amplifier: Bringing Attention to Neglected Low-Energy Components in Time Series Forecasting
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TimePFN: Effective Multivariate Time Series Forecasting with Synthetic Data
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TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation
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Adapting Large Language Models for Time Series Modeling via a Novel Parameter-efficient Adaptation Method
- 19 Feb 2025, Juyuan Zhang, et al.
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AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting
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Harnessing Vision Models for Time Series Analysis: A Survey
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HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting
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Are KANs Effective for Multivariate Time Series Forecasting?
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xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition
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IN-Flow: Instance Normalization Flow for Non-stationary Time Series Forecasting
- 06 Feb 2025, Wei Fan, et al.
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Error-quantified Conformal Inference for Time Series
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FreEformer: Frequency Enhanced Transformer for Multivariate Time Series Forecasting
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TVNet: A Novel Time Series Analysis Method Based on Dynamic Convolution and 3D-Variation
- 23 Jan 2025, Chenghan Li, et al.
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TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting
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Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching
- 14 Jan 2025, Meng Wang, et al.
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Battling the Non-stationarity in Time Series Forecasting via Test-time Adaptation
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The Tabular Foundation Model TabPFN Outperforms Specialized Time Series Forecasting Models Based on Simple Features
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Context-Alignment: Activating and Enhancing LLM Capabilities in Time Series
- 07 Jan 2025, Yuxiao Hu, et al.
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LMS-AutoTSF: Learnable Multi-Scale Decomposition and Integrated Autocorrelation for Time Series Forecasting
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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences
- 06 Jan 2025, Xiwen Chen, et al.
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AverageLinear: Enhance Long-Term Time series forcasting with simple averaging
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TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting
- 30 Dec 2024, Huanyu Zhang, et al.
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Unlocking the Power of Patch: Patch-Based MLP for Long-Term Time Series Forecasting
- 25 Dec 2024, Peiwang Tang, et al.
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Hierarchical Classification Auxiliary Network for Time Series Forecasting
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DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting
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WPMixer: Efficient Multi-Resolution Mixing for Long-Term Time Series Forecasting
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TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation
- 21 Dec 2024, Silin Yang, et al.
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Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine
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CSformer: Combining Channel Independence and Mixing for Robust Multivariate Time Series Forecasting
- 17 Dec 2024, Haoxin Wang, et al.
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LiNo: Advancing Recursive Residual Decomposition of Linear and Nonlinear Patterns for Robust Time Series Forecasting
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TimeCHEAT: A Channel Harmony Strategy for Irregularly Sampled Multivariate Time Series Analysis
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ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual Data
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ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis
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Auto-Regressive Moving Diffusion Models for Time Series Forecasting
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Rethinking Time Series Forecasting with LLMs via Nearest Neighbor Contrastive Learning
- 06 Dec 2024, Jayanie Bogahawatte, et al.
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Disentangled Interpretable Representation for Efficient Long-term Time Series Forecasting
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Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective
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Scaling Law for Time Series Forecasting
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EffiCANet: Efficient Time Series Forecasting with Convolutional Attention
- 07 Nov 2024, Xinxing Zhou, et al.
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Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis
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From Similarity to Superiority: Channel Clustering for Time Series Forecasting
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A Mamba Foundation Model for Time Series Forecasting
- 05 Nov 2024, Haoyu Ma, et al.
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Cross-Domain Pre-training with Language Models for Transferable Time Series Representations
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Not All Frequencies Are Created Equal:Towards a Dynamic Fusion of Frequencies in Time-Series Forecasting
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ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer
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FilterNet: Harnessing Frequency Filters for Time Series Forecasting
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Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting
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FlexTSF: A Universal Forecasting Model for Time Series with Variable Regularities
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From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection
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Sequential Order-Robust Mamba for Time Series Forecasting
- 30 Oct 2024, Seunghan Lee, et al.
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LTBoost: Boosted Hybrids of Ensemble Linear and Gradient Algorithms for the Long-term Time Series Forecasting
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TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis
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HiPPO-KAN: Efficient KAN Model for Time Series Analysis
- 19 Oct 2024, SangJong Lee, et al.
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Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting
- 16 Oct 2024, Jinliang Deng, et al.
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FoundTS: Comprehensive and Unified Benchmarking of Foundation Models for Time Series Forecasting
- 15 Oct 2024, Zhe Li, et al.
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LLM-Mixer: Multiscale Mixing in LLMs for Time Series Forecasting
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Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts
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Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift
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Are Self-Attentions Effective for Time Series Forecasting?
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Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models
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TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting
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Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
- 08 Oct 2024, Qingxiang Liu, et al.
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Timer-XL: Long-Context Transformers for Unified Time Series Forecasting
- 07 Oct 2024, Yong Liu, et al.
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Autoregressive Moving-average Attention Mechanism for Time Series Forecasting
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MMFNet: Multi-Scale Frequency Masking Neural Network for Multivariate Time Series Forecasting
- 02 Oct 2024, Aitian Ma, et al.
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NuwaTS: a Foundation Model Mending Every Incomplete Time Series
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Frequency Adaptive Normalization For Non-stationary Time Series Forecasting
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Evolving Multi-Scale Normalization for Time Series Forecasting under Distribution Shifts
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CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns
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CMamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series Forecasting
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PGN: The RNN’s New Successor is Effective for Long-Range Time Series Forecasting
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Double-Path Adaptive-correlation Spatial-Temporal Inverted Transformer for Stock Time Series Forecasting
- 24 Sep 2024, Wenbo Yan, et al.
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Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
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D2Vformer: A Flexible Time Series Prediction Model Based on Time Position Embedding
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TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model
- 03 Sep 2024, Defu Cao, et al.
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VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters
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Mamba or Transformer for Time Series Forecasting? Mixture of Universals (MoU) Is All You Need
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PRformer: Pyramidal Recurrent Transformer for Multivariate Time Series Forecasting
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Unlocking the Power of LSTM for Long Term Time Series Forecasting
- 19 Aug 2024, Yaxuan Kong, et al.
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Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators
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Bidirectional Generative Pre-training for Improving Time Series Representation Learning
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Scalable Transformer for High Dimensional Multivariate Time Series Forecasting
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RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms
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Fine-grained Attention in Hierarchical Transformers for Tabular Time-series
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HiMTM: Hierarchical Multi-Scale Masked Time Series Modeling with Self-Distillation for Long-Term Forecasting
- 01 Aug 2024, Shubao Zhao, et al.
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DAM: Towards A Foundation Model for Time Series Forecasting
- 25 Jul 2024, Luke Darlow, et al.
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A Survey of Explainable Artificial Intelligence (XAI) in Financial Time Series Forecasting
- 22 Jul 2024, Pierre-Daniel Arsenault, et al.
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Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization
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Deep Time Series Models: A Comprehensive Survey and Benchmark
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Long Input Sequence Network for Long Time Series Forecasting
- 18 Jul 2024, Chao Ma, et al.
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Revisiting Attention for Multivariate Time Series Forecasting
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Large Pre-trained time series models for cross-domain Time series analysis tasks
- 11 Jul 2024, Harshavardhan Kamarthi, et al.
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Loss Shaping Constraints for Long-Term Time Series Forecasting
- 11 Jul 2024, Ignacio Hounie, et al.
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ViTime: A Visual Intelligence-Based Foundation Model for Time Series Forecasting
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S2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
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Fredformer: Frequency Debiased Transformer for Time Series Forecasting
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Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling
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Addressing Prediction Delays in Time Series Forecasting: A Continuous GRU Approach with Derivative Regularization
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Deep Frequency Derivative Learning for Non-stationary Time Series Forecasting
- 29 Jun 2024, Wei Fan, et al.
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SigKAN: Signature-Weighted Kolmogorov-Arnold Networks for Time Series
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Are Language Models Actually Useful for Time Series Forecasting?
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DeciMamba: Exploring the Length Extrapolation Potential of Mamba
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Understanding Different Design Choices in Training Large Time Series Models
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Omni-Dimensional Frequency Learner for General Time Series Analysis
- 19 Jul 2024, Xianing Chen, et al.
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Foundation Models for Time Series Analysis: A Tutorial and Survey
- 18 Jun 2024, Yuxuan Liang, et al.
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Generative Pretrained Hierarchical Transformer for Time Series Forecasting
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ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons
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LLMFactor: Extracting Profitable Factors through Prompts for Explainable Stock Movement Prediction
- 16 Jun 2024, Meiyun Wang, et al.
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RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data
- 12 Jun 2024, Chin-Chia Michael Yeh, et al.
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SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion
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Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis
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A Survey on Diffusion Models for Time Series and Spatio-Temporal Data
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Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift
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When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting
- 07 Jun 2024, Zijian Li, et al.
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Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting
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Kolmogorov-Arnold Networks for Time Series: Bridging Predictive Power and Interpretability
- 04 Jun 2024, Kunpeng Xu, et al.
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Timer: Generative Pre-trained Transformers Are Large Time Series Models
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SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention
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SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
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BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition
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Efficient and Effective Time-Series Forecasting with Spiking Neural Networks
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UNITS: A Unified Multi-Task Time Series Model
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ForecastGrapher: Redefining Multivariate Time Series Forecasting with Graph Neural Networks
- 28 May 2024, Wanlin Cai, et al.
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MambaTS: Improved Selective State Space Models for Long-term Time Series Forecasting
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CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning
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TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
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GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing
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Bi-Mamba+: Bidirectional Mamba for Time Series Forecasting
- 17 May 2024, Aobo Liang, et al.
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DGCformer: Deep Graph Clustering Transformer for Multivariate Time Series Forecasting
- 14 May 2024, Qinshuo Liu, et al.
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Multi-Scale Dilated Convolution Network for Long-Term Time Series Forecasting
- 14 May 2024, Feifei Li, et al
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Kolmogorov-Arnold Networks (KANs) for Time Series Analysis
- 14 May 2024, Cristian J. Vaca-Rubio, et al.
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TKAN: Temporal Kolmogorov-Arnold Networks
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DTMamba : Dual Twin Mamba for Time Series Forecasting
- 11 May 2024, Zexue Wu, et al.
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Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting
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T-Rep: Representation Learning for Time Series using Time-Embeddings
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A Survey of Time Series Foundation Models: Generalizing Time Series Representation with Large Language Model
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TSLANet: Rethinking Transformers for Time Series Representation Learning
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Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach
- 02 May 2024, Weijia Zhang, et al.
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Integrating Mamba and Transformer for Long-Short Range Time Series Forecasting
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