csinva/hierarchical-dnn-interpretations
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
129 stars. No commits in the last 6 months.
Stars
129
Forks
22
Language
Jupyter Notebook
License
MIT
Last pushed
Aug 25, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/csinva/hierarchical-dnn-interpretations"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
obss/sahi
Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
understandable-machine-intelligence-lab/Quantus
Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
MAIF/shapash
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent...
ModelOriented/DALEX
moDel Agnostic Language for Exploration and eXplanation
csinva/imodels
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling...