:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	You, Jiang, Cela, Arben, Natowicz, René, Ouanounou, Jacob, Siarry, Patrick
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2410.02438
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Kernel-U-Net: Multivariate Time Series Forecasting using Custom Kernels
by: You, Jiang, et al.
Published: (2024)

Robust Time Series Forecasting with Non-Heavy-Tailed Gaussian Loss-Weighted Sampler
by: You, Jiang, et al.
Published: (2024)

Anomaly Prediction: A Novel Approach with Explicit Delay and Horizon
by: You, Jiang, et al.
Published: (2024)

Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series
by: You, Jiang, et al.
Published: (2025)

Foundation models for time series forecasting: Application in conformal prediction
by: Achour, Sami, et al.
Published: (2025)

Are Data Embeddings effective in time series forecasting?
by: Nematirad, Reza, et al.
Published: (2025)

Optimal starting point for time series forecasting
by: Zhong, Yiming, et al.
Published: (2024)

Automated univariate time series forecasting with regression trees
by: Martínez, Francisco, et al.
Published: (2026)

Mamba time series forecasting with uncertainty quantification
by: Pessoa, Pedro, et al.
Published: (2025)

Adaptive time series forecasting with markovian variance switching
by: Abélès, Baptiste, et al.
Published: (2024)

Can time series forecasting be automated? A benchmark and analysis
by: Sreedhara, Anvitha Thirthapura, et al.
Published: (2024)

Automatic selection of the best neural architecture for time series forecasting
by: Cao, Qianying, et al.
Published: (2025)

PRISM: A hierarchical multiscale approach for time series forecasting
by: Chen, Zihao, et al.
Published: (2025)

Intermittent time series forecasting: local vs global models
by: Damato, Stefano, et al.
Published: (2026)

Explainable time-series forecasting with sampling-free SHAP for Transformers
by: Hertel, Matthias, et al.
Published: (2025)

Grey-informed neural network for time-series forecasting
by: Xie, Wanli, et al.
Published: (2024)

KANMixer: a minimal KAN-centered mixer for long-term time series forecasting
by: Jiang, Lingyu, et al.
Published: (2025)

Differentiable latent structure discovery for interpretable forecasting in clinical time series
by: Lerner, Ivan, et al.
Published: (2026)

Augmented Invertible Koopman Autoencoder for long-term time series forecasting
by: Frion, Anthony, et al.
Published: (2025)

WaveCastNet: Rapid Wavefield Forecasting for Earthquake Early Warning via Deep Sequence to Sequence Learning
by: Lyu, Dongwei, et al.
Published: (2024)

Universal time-series forecasting with mixture predictors
by: Ryabko, Daniil
Published: (2020)

Two-stage hybrid models for enhancing forecasting accuracy on heterogeneous time series
by: Ren, Junru, et al.
Published: (2025)

Statistical benchmarking of transformer models in low signal-to-noise time-series forecasting
by: Garcia, Cyril, et al.
Published: (2026)

Hypercomplex neural network in time series forecasting of stock data
by: Kycia, Radosław, et al.
Published: (2024)

Less is more: Embracing sparsity and interpolation with Esiformer for time series forecasting
by: Guo, Yangyang, et al.
Published: (2024)

Chain-structured neural architecture search for financial time series forecasting
by: Levchenko, Denis, et al.
Published: (2024)

DeepTSF: Codeless machine learning operations for time series forecasting
by: Pelekis, Sotiris, et al.
Published: (2023)

Enhancing few-shot time series forecasting with LLM-guided diffusion
by: Shi, Haonan, et al.
Published: (2026)

A projected nonlinear state-space model for forecasting time series signals
by: Donner, Christian, et al.
Published: (2023)

The impact of data set similarity and diversity on transfer learning success in time series forecasting
by: Ehrig, Claudia, et al.
Published: (2024)

A decoder-only foundation model for time-series forecasting
by: Das, Abhimanyu, et al.
Published: (2023)

A federated large language model for long-term time series forecasting
by: Abdel-Sater, Raed, et al.
Published: (2024)

WEITS: A Wavelet-enhanced residual framework for interpretable time series forecasting
by: Guo, Ziyou, et al.
Published: (2024)

The Bayesian Context Trees State Space Model for time series modelling and forecasting
by: Papageorgiou, Ioannis, et al.
Published: (2023)

What is the best RNN-cell structure to forecast each time series behavior?
by: Khaldi, Rohaifa, et al.
Published: (2022)

Drought forecasting using a hybrid neural architecture for integrating time series and static data
by: Agudelo, Julian, et al.
Published: (2025)

A general framework for multi-step ahead adaptive conformal heteroscedastic time series forecasting
by: Sousa, Martim, et al.
Published: (2022)

S4M: S4 for multivariate time series forecasting with Missing values
by: Peng, Jing, et al.
Published: (2025)

Time series forecasting with Hahn Kolmogorov-Arnold networks
by: Hasan, Md Zahidul, et al.
Published: (2026)

CNN-TFT explained by SHAP with multi-head attention weights for time series forecasting
by: Stefenon, Stefano F., et al.
Published: (2025)