ICML 2024 "time series forecasting" Papers
11 papers found
$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
Zijie Pan, Yushan Jiang, Sahil Garg et al.
ICML 2024oral
An Analysis of Linear Time Series Forecasting Models
William Toner, Luke Darlow
ICML 2024poster
Explain Temporal Black-Box Models via Functional Decomposition
Linxiao Yang, Yunze Tong, Xinyue Gu et al.
ICML 2024oral
Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach
Weijia Zhang, Chenlong Yin, Hao Liu et al.
ICML 2024oral
Loss Shaping Constraints for Long-Term Time Series Forecasting
Ignacio Hounie, Javier Porras-Valenzuela, Alejandro Ribeiro
ICML 2024poster
Probabilistic Time Series Modeling with Decomposable Denoising Diffusion Model
Tijin Yan, Hengheng Gong, Yongping He et al.
ICML 2024poster
Reservoir Computing for Short High-Dimensional Time Series: an Application to SARS-CoV-2 Hospitalization Forecast
Thomas Ferté, Dutartre Dan, Boris Hejblum et al.
ICML 2024poster
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.
ICML 2024poster
SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting
Lu Han, Han-Jia Ye, De-Chuan Zhan
ICML 2024poster
Timer: Generative Pre-trained Transformers Are Large Time Series Models
Yong Liu, Haoran Zhang, Chenyu Li et al.
ICML 2024poster
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.
ICML 2024oral