thuml/iTransformer
Some data may be outdated — see provenance labels.
Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight) observed · 2026-10-01
Health v2 · maintenance only
39/100
- Activity 24
- Release rhythm 35
- Longevity 78
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1098
- days_rel: n/a
- days_push: 460
- n_releases_24m: 0
Adoption not part of the score
2225 stars · 373 forks observed · 2026-10-01
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Official PyTorch implementation of iTransformer, an ICLR 2024 Spotlight paper that inverts the Transformer architecture for multivariate time series forecasting by treating each variate as a token. It includes experiment scripts and achieves state-of-the-art results on standard forecasting benchmarks.
Use cases
- forecast multivariate time series with transformers
- reproduce iTransformer paper experiments
- benchmark forecasting models on time series datasets
- predict future values of multiple correlated sensors
- compare transformer baselines for long-term forecasting
When to choose
- you need a strong transformer-based multivariate forecasting baseline
- you want to reproduce or extend the iTransformer paper
- your data has many correlated variates and long lookback windows
When to avoid
- you need simple univariate forecasting where linear models suffice
- you need a production-ready forecasting service rather than research code
- you lack GPU resources for training transformer models
Facets
library · maturity stable
machine-learning deep-learning time-series machine-learning data-science python time-series-forecasting transformer research-code iclr-2024 multivariate-forecasting gpu
6 sources
- readme: https://github.com/thuml/iTransformer · fetched 2026-10-01 · 3665cd07ef37
- homepage: https://arxiv.org/abs/2310.06625 · fetched 2026-08-29 · 0882d7180727
- site_page: https://info.arxiv.org/about/donate.html · fetched 2026-08-29 · cca9c3a11c56
- site_page: https://info.arxiv.org/about/ourmembers.html · fetched 2026-08-29 · 47cbc55ff1de
- site_page: https://info.arxiv.org/about · fetched 2026-08-29 · a1f16f915a9a
- site_page: https://info.arxiv.org/labs/index.html · fetched 2026-08-29 · b14a8d05a0ec
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| thuml/iTransformer | main | 39 |
For agents
markdown · JSON · MCP: product_card(name="thuml/iTransformer")
Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem