GitHub topics: attribution-methods
Julia-XAI/ExplainableAI.jl
Explainable AI in Julia.
Language: Julia - Size: 41.2 MB - Last synced at: 2 days ago - Pushed at: 2 days ago - Stars: 112 - Forks: 3

evanseitz/squid-nn
surrogate quantitative interpretability for deepnets
Language: Python - Size: 3.82 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 21 - Forks: 1

kotiyalanurag/Exploring-Data-Augmentation-Methods-through-Attribution
Code for my Master Thesis titled "Exploring Data Augmentation Methods through Attribution".
Language: Python - Size: 2.87 MB - Last synced at: 18 days ago - Pushed at: 18 days ago - Stars: 0 - Forks: 0

inseq-team/inseq
Interpretability for sequence generation models 🐛 🔍
Language: Python - Size: 7.64 MB - Last synced at: 23 days ago - Pushed at: about 2 months ago - Stars: 419 - Forks: 38

Betswish/MIRAGE
Easy-to-use MIRAGE code for faithful answer attribution in RAG applications. Paper: https://aclanthology.org/2024.emnlp-main.347/
Language: Python - Size: 3.48 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 21 - Forks: 2

frankaging/BERT-LRP
On Explaining Your Explanations of BERT: An Empirical Study with Sequence Classification
Language: Jupyter Notebook - Size: 4.91 MB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 30 - Forks: 9

jordan7186/GAtt
Source code for the GAtt method in "Revisiting Attention Weights as Interpretations of Message-Passing Neural Networks".
Language: Jupyter Notebook - Size: 1.35 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 1

kgourgou/setfit-integrated-gradients
Hacking SetFit so that it works with integrated gradients.
Language: Python - Size: 57.6 KB - Last synced at: about 2 months ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 2

evanseitz/squid-manuscript
squid repository for manuscript analysis
Language: Python - Size: 165 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

Piyushi-0/ACE
Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.
Language: Jupyter Notebook - Size: 77.2 MB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 49 - Forks: 19

Piyushi-0/SEA-NN
Code for our NN Attribution work accepted at AISTATS '22
Language: Jupyter Notebook - Size: 651 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

sukrutrao/Attribution-Evaluation
Code for the paper: Towards Better Understanding Attribution Methods. CVPR 2022.
Language: Python - Size: 1.03 MB - Last synced at: over 2 years ago - Pushed at: about 3 years ago - Stars: 8 - Forks: 2

saurabheights/ROAR
Metrics for evaluating interpretability methods.
Language: Python - Size: 61.5 KB - Last synced at: over 2 years ago - Pushed at: about 4 years ago - Stars: 4 - Forks: 0

shinkyo0513/Towards-Visually-Explaining-Video-Understanding-Networks-With-Perturbation
Attribution (or visual explanation) methods for understanding video classification networks. Demo codes for WACV2021 paper: Towards Visually Explaining Video Understanding Networks with Perturbation.
Language: Python - Size: 166 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 15 - Forks: 0

shinkyo0513/Spatio-Temporal-Perturbations-for-Video-Attribution
The source code for the journal paper: Spatio-Temporal Perturbations for Video Attribution, TCSVT-2021
Language: Python - Size: 36.9 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
