Frequency-domain MLPs are More Effective Learners in Time Series Forecasting

Nov-20-2025, 00:38:19 GMT–Neural Information Processing Systems

Then, we propose FreTS, a simple yet effective architecture built upon Fre quency-domain MLPs for T ime S eries forecasting.

data mining, forecasting, machine learning, (18 more...)

Neural Information Processing Systems

Nov-20-2025, 00:38:19 GMT

Conferences PDF

Country:
- Asia
  - China
    - Anhui Province > Hefei (0.04)
    - Beijing > Beijing (0.04)
  - Japan (0.04)
  - Macao (0.04)
  - Singapore (0.04)
- Europe
  - Germany (0.04)
  - Switzerland (0.04)
  - United Kingdom > England
    - Oxfordshire > Oxford (0.04)
- North America
  - Canada (0.04)
  - Trinidad and Tobago > Trinidad
    - Arima > Arima (0.04)
  - United States
    - California
      - Los Angeles County (0.04)
      - San Francisco County > San Francisco (0.04)
    - Massachusetts (0.04)
- Oceania
  - Australia (0.04)
  - New Zealand (0.04)

Genre:
- Research Report > New Finding (0.46)

Industry:
- Energy (1.00)

Technology:
- Information Technology
  - Artificial Intelligence
    - Machine Learning > Neural Networks
      - Deep Learning (1.00)
    - Representation & Reasoning (0.67)
  - Communications (1.00)
  - Data Science > Data Mining (0.84)

Duplicate Docs Excel Report

Title
Frequency-domain MLPs are More Effective Learners in Time Series Forecasting

Similar Docs Excel Report more

Title	Similarity	Source
None found