scene-representation-diffusion-model

A game theoretic approach to explain the output of any machine learning model.

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

Official implementations for paper: Anydoor: zero-shot object-level image customization

? Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

Algorithms for explaining machine learning models

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)

? InfiniteYou: Flexible Photo Recrafting While Preserving Your Identity

[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

A JAX research toolkit for building, editing, and visualizing neural networks.

Model explainability that works seamlessly with ? transformers. Explain your transformers model in just 2 lines of code.