Downloads · 30 days
0
reservoir-chaos-pocket-lab
ARotting/reservoir-chaos-pocket-lab
reservoir-chaos-pocket-lab is a machine learning model from ARotting. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Reservoir Chaos Pocket fits an Echo State Network to the Lorenz-63 attractor. The recurrent reservoir is fixed after spectral-radius scaling; only the linear readout is trained, in one ridge-regression solve. Linear a…
Access
Public
Updated Jul 30, 2026
Repo size
174 KB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.parquet103 KB · 48%
At a glance
- Access
- Public
- Created
- Jul 30, 2026
- Updated
- Jul 30, 2026
- SHA
- 3dd6c415
Model card
From the Hugging Face model README
Reservoir Chaos Pocket
Reservoir Chaos Pocket fits an Echo State Network to the Lorenz-63 attractor. The recurrent reservoir is fixed after spectral-radius scaling; only the linear readout is trained, in one ridge-regression solve. Linear autoregression and persistence are explicit controls.
Evaluation measures teacher-forced one-step RMSE and the first closed-loop step where normalized vector error exceeds 0.4. The Space visualizes how rapidly each forecast diverges on a chaotic trajectory.
Verified local result
The fixed 128-unit reservoir stores 17,292 values but trains only its 396-value readout. It reached 0.0165 one-step RMSE and a 38-step closed-loop horizon, versus 0.299/2 for 12-parameter linear autoregression and 0.358/2 for persistence.
uv run python projects/reservoir-chaos-pocket/train.py
uv run pytest tests/test_reservoir_chaos_pocket.py
Hosted showcase
This free static Space preserves the complete original Gradio source, trained artifacts, evaluation files, and local launch requirements. Hugging Face now requires PRO for CPU-backed Gradio hosting, so the public landing page is static while the checked-in app.py remains the authoritative runnable demo.
- Created
- Jul 30, 2026
- Updated
- Jul 30, 2026