Statistics for topic interpretability
RepositoryStats tracks 595,857 Github repositories, of these 169 are tagged with the interpretability topic. The most common primary language for repositories using this topic is Python (84). Other languages include: Jupyter Notebook (46)
Stargazers over time for topic interpretability
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A game theoretic approach to explain the output of any machine learning model.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
[NeurIPS 2024] Knowledge Circuits in Pretrained Transformers
Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction - CVPR 2024
The nnsight package enables interpreting and manipulating the internals of deep learned models.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
A game theoretic approach to explain the output of any machine learning model.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
[NeurIPS 2024] Knowledge Circuits in Pretrained Transformers
For OpenMOSS Mechanistic Interpretability Team's Sparse Autoencoder (SAE) research.
A game theoretic approach to explain the output of any machine learning model.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
[NeurIPS 2024] Knowledge Circuits in Pretrained Transformers
For OpenMOSS Mechanistic Interpretability Team's Sparse Autoencoder (SAE) research.
Code for the paper "Aligning LLM Agents by Learning Latent Preference from User Edits".
A JAX research toolkit for building, editing, and visualizing neural networks.
An awesome repository & A comprehensive survey on interpretability of LLM attention heads.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
A game theoretic approach to explain the output of any machine learning model.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
A JAX research toolkit for building, editing, and visualizing neural networks.
The Truth Is In There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
The nnsight package enables interpreting and manipulating the internals of deep learned models.
Decomposing and Editing Predictions by Modeling Model Computation
A list of (post-hoc) XAI for time series