Ecosyste.ms: Repos
An open API service providing repository metadata for many open source software ecosystems.
GitHub topics: attribution-methods
inseq-team/inseq
Interpretability for sequence generation models 🐛 🔍
Language: Python - Size: 5.61 MB - Last synced: 5 days ago - Pushed: 5 days ago - Stars: 322 - Forks: 35
Julia-XAI/ExplainableAI.jl
Explainable AI in Julia.
Language: Julia - Size: 39.1 MB - Last synced: 24 days ago - Pushed: 3 months ago - Stars: 99 - Forks: 2
evanseitz/squid-nn
surrogate quantitative interpretability for deepnets
Language: Python - Size: 3.79 MB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 9 - Forks: 1
evanseitz/squid-manuscript
squid repository for manuscript analysis
Language: Python - Size: 165 MB - Last synced: 3 months ago - Pushed: 3 months 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: 5 months ago - Pushed: over 2 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: 7 months ago - Pushed: 7 months ago - Stars: 1 - Forks: 0
kgourgou/setfit-integrated-gradients
Hacking SetFit so that it works with integrated gradients.
Language: Python - Size: 57.6 KB - Last synced: 10 months ago - Pushed: 10 months ago - Stars: 0 - Forks: 2
sukrutrao/Attribution-Evaluation
Code for the paper: Towards Better Understanding Attribution Methods. CVPR 2022.
Language: Python - Size: 1.03 MB - Last synced: about 1 year ago - Pushed: almost 2 years ago - Stars: 8 - Forks: 2
saurabheights/ROAR
Metrics for evaluating interpretability methods.
Language: Python - Size: 61.5 KB - Last synced: over 1 year ago - Pushed: about 3 years ago - Stars: 4 - Forks: 0
frankaging/BERT-LRP
On Explaining Your Explanations of BERT: An Empirical Study with Sequence Classification
Language: Jupyter Notebook - Size: 4.91 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 22 - Forks: 6
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: about 1 year ago - Pushed: over 1 year 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: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0