:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Do, Bach Viet, Li, Xingyu, Pan, Chaoye
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2407.16739
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Tackling Data Heterogeneity in Federated Time Series Forecasting
by: Yuan, Wei, et al.
Published: (2024)

Reviving Error Correction in Modern Deep Time-Series Forecasting
by: Nguyen, Minh Hoang, et al.
Published: (2026)

Forecasting Supply Chain Disruptions with Foresight Learning
by: Turtel, Benjamin, et al.
Published: (2026)

Simple Contrastive Representation Learning for Time Series Forecasting
by: Zheng, Xiaochen, et al.
Published: (2023)

Time-Prompt: Integrated Heterogeneous Prompts for Unlocking LLMs in Time Series Forecasting
by: Wang, Zesen, et al.
Published: (2025)

PHAT: Modeling Period Heterogeneity for Multivariate Time Series Forecasting
by: Ma, Jiaming, et al.
Published: (2026)

Improving Forecasts for Heterogeneous Time Series by "Averaging", with Application to Food Demand Forecast
by: Neubauer, Lukas, et al.
Published: (2023)

Bridging Theory and Practice: A Stochastic Learning-Optimization Model for Resilient Automotive Supply Chains
by: Shahnawaz, Muhammad, et al.
Published: (2025)

Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting
by: Dong, Zheng, et al.
Published: (2024)

EasyTime: Time Series Forecasting Made Easy
by: Qiu, Xiangfei, et al.
Published: (2024)

Accelerating Long-Term Molecular Dynamics with Physics-Informed Time-Series Forecasting
by: Le, Hung, et al.
Published: (2025)

Closing the Loop: A Control-Theoretic Framework for Provably Stable Time Series Forecasting with LLMs
by: Zhang, Xingyu, et al.
Published: (2026)

TS-LIF: A Temporal Segment Spiking Neuron Network for Time Series Forecasting
by: Feng, Shibo, et al.
Published: (2025)

Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting
by: Kang, Bong Gyun, et al.
Published: (2024)

Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity
by: Kamarthi, Harshavardhan, et al.
Published: (2024)

Beyond All-to-All: Causal-Aligned Transformer with Dynamic Structure Learning for Multivariate Time Series Forecasting
by: Zhang, Xingyu, et al.
Published: (2025)

Not All Frequencies Are Created Equal:Towards a Dynamic Fusion of Frequencies in Time-Series Forecasting
by: Zhang, Xingyu, et al.
Published: (2024)

Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis
by: Shao, Zezhi, et al.
Published: (2023)

MoHETS: Long-term Time Series Forecasting with Mixture-of-Heterogeneous-Experts
by: Ortigossa, Evandro S., et al.
Published: (2026)

Joint Time Series Chain: Detecting Unusual Evolving Trend across Time Series
by: Zhang, Li, et al.
Published: (2026)

Forecasting with Guidance: Representation-Level Supervision for Time Series Forecasting
by: Wang, Jiacheng, et al.
Published: (2026)

CC-Time: Cross-Model and Cross-Modality Time Series Forecasting
by: Chen, Peng, et al.
Published: (2025)

Neural Conformal Control for Time Series Forecasting
by: Li, Ruipu, et al.
Published: (2024)

LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling
by: Pan, Sheng, et al.
Published: (2026)

Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models
by: Wang, Hao, et al.
Published: (2025)

Structural Knowledge Informed Continual Multivariate Time Series Forecasting
by: Pan, Zijie, et al.
Published: (2024)

ISOMORPH: A Supply Chain Digital Twin for Simulation, Dataset Generation, and Forecasting Benchmarks
by: Zhang, Zhizhen, et al.
Published: (2026)

TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting
by: Hu, Yifan, et al.
Published: (2025)

AWEMixer: Adaptive Wavelet-Enhanced Mixer Network for Long-Term Time Series Forecasting
by: Li, Qianyang, et al.
Published: (2025)

ECoLAD: Deployment-Oriented Evaluation for Automotive Time-Series Anomaly Detection
by: Özer, Kadir-Kaan, et al.
Published: (2026)

Hybrid Deep Learning Approach for Coupled Demand Forecasting and Supply Chain Optimization
by: Nadia, Nusrat Yasmin, et al.
Published: (2026)

LETS Forecast: Learning Embedology for Time Series Forecasting
by: Majeedi, Abrar, et al.
Published: (2025)

Scaling Law for Time Series Forecasting
by: Shi, Jingzhe, et al.
Published: (2024)

Contrast All the Time: Learning Time Series Representation from Temporal Consistency
by: Shamba, Abdul-Kazeem, et al.
Published: (2024)

Forecasting Multivariate Time Series under Predictive Heterogeneity: A Validation-Driven Clustering Framework
by: Ma, Ziling, et al.
Published: (2026)

It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks
by: Qiao, Zhongzheng, et al.
Published: (2026)

EventTSF: Event-Aware Non-Stationary Time Series Forecasting
by: Ge, Yunfeng, et al.
Published: (2025)

Deep Autocorrelation Modeling for Time-Series Forecasting: Progress and Prospects
by: Wang, Hao, et al.
Published: (2026)

N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting
by: Matos, Ricardo, et al.
Published: (2025)

Selective Learning for Deep Time Series Forecasting
by: Fu, Yisong, et al.
Published: (2025)