Renewable-Thermal-Laboratory/CSP-Thermo-PGML
PGNN and PG-LSTM models for predicting and forecasting temperature profiles in CSP volumetric receivers.
Stars
—
Forks
—
Language
Jupyter Notebook
License
—
Last pushed
Apr 08, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Renewable-Thermal-Laboratory/CSP-Thermo-PGML"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
fastapi/fastapi
FastAPI framework, high performance, easy to learn, fast to code, ready for production
scikit-learn/scikit-learn
scikit-learn: machine learning in Python
probabl-ai/skore
Track your Data Science. Skore's open-source Python library accelerates ML model development...
Farama-Foundation/Gymnasium
An API standard for single-agent reinforcement learning environments, with popular reference...
WMD-group/SMACT
Python package to aid materials design and informatics