#计算机科学#A game theoretic approach to explain the output of any machine learning model.
#Awesome#A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
#计算机科学#Fit interpretable models. Explain blackbox machine learning.
#计算机科学#🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
#计算机科学#[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.
#计算机科学#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 libr...
#计算机科学#XAI - An eXplainability toolbox for machine learning
[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-bas...
#时序数据库#Power Tools for AI Engineers With Deadlines
#计算机科学#Visualization toolkit for neural networks in PyTorch! Demo -->
#计算机科学#Papers about explainability of GNNs
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
#计算机科学#Shapley Interactions and Shapley Values for Machine Learning
#计算机科学#Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ ms...
CLIP Surgery for Better Explainability with Enhancement in Open-Vocabulary Tasks
Official implementation of Score-CAM in PyTorch
This is an open-source version of the representation engineering framework for stopping harmful outputs or hallucinations on the level of activations. 100% free, self-hosted and open-source.
#计算机科学#Neural network visualization toolkit for tf.keras
💡 Adversarial attacks on explanations and how to defend them
#计算机科学#CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms