Cover Image

Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Masserano, Luca, Ansari, Abdul Fatir, Han, Boran, Zhang, Xiyuan, Faloutsos, Christos, Mahoney, Michael W., Wilson, Andrew Gordon, Park, Youngsuk, Rangapuram, Syama, Maddix, Danielle C., Wang, Yuyang
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Understanding the Implicit Biases of Design Choices for Time Series Foundation Models
by: Yu, Annan, et al.
Published: (2025)

Understanding Transformers for Time Series: Rank Structure, Flow-of-ranks, and Compressibility
by: Yu, Annan, et al.
Published: (2025)

Gradient-Free Generation for Hard-Constrained Systems
by: Cheng, Chaoran, et al.
Published: (2024)

When Does Multimodality Lead to Better Time Series Forecasting?
by: Zhang, Xiyuan, et al.
Published: (2025)

Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting
by: Hasson, Hilaf, et al.
Published: (2023)

Zero-Shot Time Series Forecasting with Covariates via In-Context Learning
by: Auer, Andreas, et al.
Published: (2025)

Comparing and Contrasting DLWP Backbones on Navier-Stokes and Atmospheric Dynamics
by: Karlbauer, Matthias, et al.
Published: (2024)

Mitra: Mixed Synthetic Priors for Enhancing Tabular Foundation Models
by: Zhang, Xiyuan, et al.
Published: (2025)

Chronos: Learning the Language of Time Series
by: Ansari, Abdul Fatir, et al.
Published: (2024)

ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables
by: Arango, Sebastian Pineda, et al.
Published: (2025)

Transferring Knowledge from Large Foundation Models to Small Downstream Models
by: Qiu, Shikai, et al.
Published: (2024)

Chronos-2: From Univariate to Universal Forecasting
by: Ansari, Abdul Fatir, et al.
Published: (2025)

SenTSR-Bench: Thinking with Injected Knowledge for Time-Series Reasoning
by: He, Zelin, et al.
Published: (2026)

fev-bench: A Realistic Benchmark for Time Series Forecasting
by: Shchur, Oleksandr, et al.
Published: (2025)

End-to-End Probabilistic Framework for Learning with Hard Constraints
by: Utkarsh, Utkarsh, et al.
Published: (2025)

Test-Time Efficient Pretrained Model Portfolios for Time Series Forecasting
by: Kayaalp, Mert, et al.
Published: (2025)

Generative Modeling with Flow-Guided Density Ratio Learning
by: Heng, Alvin, et al.
Published: (2023)

Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs
by: Mouli, S. Chandra, et al.
Published: (2024)

CurvGAD: Leveraging Curvature for Enhanced Graph Anomaly Detection
by: Grover, Karish, et al.
Published: (2025)

EBV: Electronic Bee-Veterinarian for Principled Mining and Forecasting of Honeybee Time Series
by: Hossain, Mst. Shamima, et al.
Published: (2024)

The Forecast Critic: Leveraging Large Language Models for Poor Forecast Identification
by: Bhan, Luke, et al.
Published: (2025)

Chapter Dai disegni analogici all’esplorazione in ambiente immersivo: la Stazione Autocorriere di U. Nordio
by: Masserano, Silvia
Published: (2024)

Efficiently Generating Correlated Sample Paths from Multi-step Time Series Foundation Models
by: Baron, Ethan, et al.
Published: (2025)

Large Language Models Are Zero-Shot Time Series Forecasters
by: Gruver, Nate, et al.
Published: (2023)

FraudFox: Adaptable Fraud Detection in the Real World
by: Butler, Matthew, et al.
Published: (2026)

Text Has Curvature
by: Grover, Karish, et al.
Published: (2026)

Wavelet Mixture of Experts for Time Series Forecasting
by: Zhou, Zheng, et al.
Published: (2025)

A More Realistic Evaluation of Cross-Frequency Transfer Learning and Foundation Forecasting Models
by: Olivares, Kin G., et al.
Published: (2025)

Classroom mathematics learning: Association of joy of learning and school connectedness among high school students in India
by: Syama Sasidharan, et al.
Published: (2024)

WaveMoE: A Wavelet-Enhanced Mixture-of-Experts Foundation Model for Time Series Forecasting
by: Wu, Shunyu, et al.
Published: (2026)

Probabilistic Forecasting for Building Energy Systems using Time-Series Foundation Models
by: Park, Young Jin, et al.
Published: (2025)

Stochastic Rounding for LLM Training: Theory and Practice
by: Ozkara, Kaan, et al.
Published: (2025)

Training LLMs with MXFP4
by: Tseng, Albert, et al.
Published: (2025)

GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection
by: Park, Namyong, et al.
Published: (2024)

NoRIN: Backbone-Adaptive Reversible Normalization for Time-Series Forecasting
by: Zhang, Shun, et al.
Published: (2026)

LLMForecaster: Improving Seasonal Event Forecasts with Unstructured Textual Data
by: Zhang, Hanyu, et al.
Published: (2024)

FRAUDGUESS: Spotting and Explaining New Types of Fraud in Million-Scale Financial Data
by: Cordeiro, Robson L. F., et al.
Published: (2025)

NetEffect: Discovery and Exploitation of Generalized Network Effects
by: Lee, Meng-Chieh, et al.
Published: (2022)

Goal-Oriented Time-Series Forecasting: Foundation Framework Design
by: Fechete, Luca-Andrei, et al.
Published: (2025)

AhmedML: High-Fidelity Computational Fluid Dynamics Dataset for Incompressible, Low-Speed Bluff Body Aerodynamics
by: Ashton, Neil, et al.
Published: (2024)