Thinklab-SJTU/Crossformer

Official implementation of our ICLR 2023 paper "Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting"

676 109 +0/wk

GitHub

deep-learning time-series-forecasting transformers

Trend 0

Star & Fork Trend (35 data points)

Stars

Forks

Multi-Source Signals

GitHub

stars 676

forks 109

Growth Velocity

Thinklab-SJTU/Crossformer has +0 stars this period . Velocity data will be available after more historical data is collected.

Deep analysis is being generated for this repository.

Signal-backed technical analysis will be available soon.

Metric	Crossformer	nboost	bottleneck-transformer-pytorch	mcunet
Stars	676	675	677	677
Forks	109	68	81	106
Weekly Growth	+0	+0	+0	+2
Language	Python	Python	Python	Python
Sources	1	1	1	1
License	Apache-2.0	Apache-2.0	MIT	MIT

Capability Radar vs nboost

Crossformer

nboost

Maintenance Activity 0

Last code push 860 days ago.

Community Engagement 81

Fork-to-star ratio: 16.1%. Active community forking and contributing.

Issue Burden 70

Issue data not yet available.

Growth Momentum 30

No measurable growth in the current period (first-day cold start expected).

License Clarity 95

Licensed under Apache-2.0. Permissive — safe for commercial use.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.