"time series forecasting" Papers
47 papers found
Conference
Amplifier: Bringing Attention to Neglected Low-Energy Components in Time Series Forecasting
Jingru Fei, Kun Yi, Wei Fan et al.
Auto-Regressive Moving Diffusion Models for Time Series Forecasting
Jiaxin Gao, Qinglong Cao, Yuntian Chen
Can LLMs Understand Time Series Anomalies?
Zihao Zhou, Rose Yu
Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine
Luis Roque, Vítor Cerqueira, Carlos Soares et al.
CoMRes: Semi-Supervised Time Series Forecasting Utilizing Consensus Promotion of Multi-Resolution
Yunju Cho, Jay-Yoon Lee
CUQDS: Conformal Uncertainty Quantification Under Distribution Shift for Trajectory Prediction
Huiqun Huang, Sihong He, Fei Miao
DecompNet: Enhancing Time Series Forecasting Models with Implicit Decomposition
Donghao Luo, Xue Wang
Density estimation with LLMs: a geometric investigation of in-context learning trajectories
Toni Liu, Nicolas Boulle, Raphaël Sarfati et al.
Enhancing Time Series Forecasting through Selective Representation Spaces: A Patch Perspective
Xingjian Wu, Xiangfei Qiu, Hanyin Cheng et al.
Locally Connected Echo State Networks for Time Series Forecasting
Filip Matzner, František Mráz
Multi-Modal View Enhanced Large Vision Models for Long-Term Time Series Forecasting
ChengAo Shen, Wenchao Yu, Ziming Zhao et al.
Neural Conformal Control for Time Series Forecasting
Ruipu Li, Alexander Rodríguez
Not All Data are Good Labels: On the Self-supervised Labeling for Time Series Forecasting
Yuxuan Yang, Dalin Zhang, Yuxuan Liang et al.
OLinear: A Linear Model for Time Series Forecasting in Orthogonally Transformed Domain
Wenzhen Yue, Yong Liu, Hao Wang et al.
PMLF: A Physics-Guided Multiscale Loss Framework for Structurally Heterogeneous Time Series
Xinghong Chen, Weilin Wu, Kunping Yang et al.
Selective Learning for Deep Time Series Forecasting
Yisong Fu, Zezhi Shao, Chengqing Yu et al.
SEMPO: Lightweight Foundation Models for Time Series Forecasting
Hui He, Kun Yi, Yuanchi Ma et al.
Sequence Complementor: Complementing Transformers for Time Series Forecasting with Learnable Sequences
Xiwen Chen, Peijie Qiu, Wenhui Zhu et al.
SynTSBench: Rethinking Temporal Pattern Learning in Deep Learning Models for Time Series
Qitai Tan, Yiyun Chen, Mo Li et al.
TARFVAE: Efficient One-Step Generative Time Series Forecasting via TARFLOW based VAE
Jiawen Wei, jiang lan, Pengbo Wei et al.
This Time is Different: An Observability Perspective on Time Series Foundation Models
Ben Cohen, Emaad Khwaja, Youssef Doubli et al.
TimeEmb: A Lightweight Static-Dynamic Disentanglement Framework for Time Series Forecasting
Mingyuan Xia, Chunxu Zhang, Zijian Zhang et al.
TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis
Shiyu Wang, Jiawei LI, Xiaoming Shi et al.
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
Xiaoming Shi, Shiyu Wang, Yuqi Nie et al.
Times2D: Multi-Period Decomposition and Derivative Mapping for General Time Series Forecasting
Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan
TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning
Andreas Auer, Patrick Podest, Daniel Klotz et al.
True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics
Christoph Jürgen Hemmer, Daniel Durstewitz
TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecaster
Kanghui Ning, Zijie Pan, Yu Liu et al.
WPMixer: Efficient Multi-Resolution Mixing for Long-Term Time Series Forecasting
Md Mahmuddun Nabi Murad, Mehmet Aktukmak, Yasin Yilmaz
xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition
Artyom Stitsyuk, Jaesik Choi
$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
Zijie Pan, Yushan Jiang, Sahil Garg et al.
An Analysis of Linear Time Series Forecasting Models
William Toner, Luke Darlow
Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting
Muyao Wang, Wenchao Chen, Bo Chen
Explain Temporal Black-Box Models via Functional Decomposition
Linxiao Yang, Yunze Tong, Xinyue Gu et al.
GMP-AR: Granularity Message Passing and Adaptive Reconciliation for Temporal Hierarchy Forecasting
Fan Zhou, Chen Pan, Lintao Ma et al.
Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach
Weijia Zhang, Chenlong Yin, Hao Liu et al.
Loss Shaping Constraints for Long-Term Time Series Forecasting
Ignacio Hounie, Javier Porras-Valenzuela, Alejandro Ribeiro
Probabilistic Time Series Modeling with Decomposable Denoising Diffusion Model
Tijin Yan, Hengheng Gong, Yongping He et al.
Reservoir Computing for Short High-Dimensional Time Series: an Application to SARS-CoV-2 Hospitalization Forecast
Thomas Ferté, Dutartre Dan, Boris Hejblum et al.
Root Cause Analysis in Microservice Using Neural Granger Causal Discovery
Cheng-Ming Lin, Ching Chang, Wei-Yao Wang et al.
SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention
Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov et al.
SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting
Lu Han, Han-Jia Ye, De-Chuan Zhan
Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data
YongKyung Oh, Dongyoung Lim, Sungil Kim
Timer: Generative Pre-trained Transformers Are Large Time Series Models
Yong Liu, Haoran Zhang, Chenyu Li et al.
TimesURL: Self-Supervised Contrastive Learning for Universal Time Series Representation Learning
jiexi Liu, Songcan Chen
U-mixer: An Unet-Mixer Architecture with Stationarity Correction for Time Series Forecasting
Xiang Ma, Xuemei Li, Lexin Fang et al.
UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis
Yunhao Zhang, Liu Minghao, Shengyang Zhou et al.