"time series forecasting" Papers
27 papers found
Can LLMs Understand Time Series Anomalies?
Zihao Zhou, Rose Yu
CoMRes: Semi-Supervised Time Series Forecasting Utilizing Consensus Promotion of Multi-Resolution
Yunju Cho, Jay-Yoon Lee
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.
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.
SEMPO: Lightweight Foundation Models for Time Series Forecasting
Hui He, Kun Yi, Yuanchi Ma et al.
SynTSBench: Rethinking Temporal Pattern Learning in Deep Learning Models for Time Series
Qitai Tan, Yiyun Chen, Mo Li et al.
This Time is Different: An Observability Perspective on Time Series Foundation Models
Ben Cohen, Emaad Khwaja, Youssef Doubli et al.
$S^2$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
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.