hijohnnylin/neuronpedia
open source interpretability platform 🧠
A star delta has been computed for 62,678 of 63,374 tracked repositories in this period, and only those can be ranked in it.
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Star counts measured between 02:16 and 17:23 (BKK).
open source interpretability platform 🧠
Model interpretability and understanding for PyTorch
A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
Fit interpretable models. Explain blackbox machine learning.
Interpretability for sequence generation models 🐛 🔍
S-Space: Exploring Spatial Workspace in Multimodal Models
Shapley Values and Shapley Interactions for Machine Learning
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM, Finer-CAM, LeGrad, RefineCAM)
That's all 11 repositories in this period.
