tail-unica/hopwise

Recbole extension with focus on Knowledge Graphs (KGs) and interpretability/explainability.

Language: Python - Size: 4.21 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 2 - Forks: 1

cwangrun/MGProto

[TPAMI 2025] Mixture of Gaussian-distributed Prototypes with Generative Modelling for Interpretable and Trustworthy Image Recognition

Language: Python - Size: 2.5 MB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 7 - Forks: 0

Trustworthy-ML-Lab/posthoc-generative-cbm

[CVPR 2025] Concept Bottleneck Autoencoder (CB-AE) -- efficiently transform any pretrained (black-box) image generative model into an interpretable generative concept bottleneck model (CBM) with minimal concept supervision, while preserving image quality

Language: Jupyter Notebook - Size: 3 MB - Last synced at: 26 days ago - Pushed at: 26 days ago - Stars: 7 - Forks: 1

shuyang-dong/Counterfactual_Explanation_for_RL

Counterfactual explanations for continuous reinforcement learning with simulation in T1D and Gym environments.

Language: Python - Size: 33.9 MB - Last synced at: 29 days ago - Pushed at: 29 days ago - Stars: 0 - Forks: 1

HennyJie/IBGNN

MICCAI 2022 (Oral): Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis

Language: Python - Size: 890 KB - Last synced at: 3 days ago - Pushed at: about 2 years ago - Stars: 58 - Forks: 7

bgreenwell/ebm

Explainable Boosting Machines

Language: R - Size: 44.5 MB - Last synced at: about 1 month ago - Pushed at: 3 months ago - Stars: 3 - Forks: 1

ruizheliUOA/Awesome-Interpretability-in-Large-Language-Models

This repository collects all relevant resources about interpretability in LLMs

Size: 63.5 KB - Last synced at: 29 days ago - Pushed at: 7 months ago - Stars: 343 - Forks: 24

Skyyyy0920/FGAI

Language: Python - Size: 1.89 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

liugangcode/GREA

[KDD'22] Source codes of "Graph Rationalization with Environment-based Augmentations"

Language: Python - Size: 145 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 38 - Forks: 6

warisgill/TraceFL

TraceFL is a novel mechanism for Federated Learning that achieves interpretability by tracking neuron provenance. It identifies clients responsible for global model predictions, achieving 99% accuracy across diverse datasets (e.g., medical imaging) and neural networks (e.g., GPT).

Language: Python - Size: 3.96 MB - Last synced at: 2 months ago - Pushed at: 7 months ago - Stars: 9 - Forks: 0

cwangrun/ST-ProtoPNet

[ICCV 2023] Learning Support and Trivial Prototypes for Interpretable Image Classification

Language: Python - Size: 841 KB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 20 - Forks: 2

bishwamittra/nus_thesis

My PhD thesis in NUS. Making it public so that future graduate students may benefit.

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vdlad/Remarkable-Robustness-of-LLMs

Codebase the paper "The Remarkable Robustness of LLMs: Stages of Inference?"

Language: Jupyter Notebook - Size: 4.05 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 9 - Forks: 0

fguzman82/PhD-Thesis

Interpretability: Methods for Identification and Retrieval of Concepts in CNN Networks

Language: Jupyter Notebook - Size: 101 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0

MattScicluna/interpretable_tsne

Implementation of the gradient-based t-SNE sttribution method described in our GLBIO oral presentation: 'Towards Computing Attributions for Dimensionality Reduction Techniques'

Language: Python - Size: 7.8 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 1

Wuyxin/DISC

Official code of "Discover and Cure: Concept-aware Mitigation of Spurious Correlation" (ICML 2023)

Language: Python - Size: 294 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 32 - Forks: 5

goz1985/RST-ARM-GLM_-Research

Work on combining Logit model with an information granulation method for better interpretability

Language: R - Size: 286 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

DimitrisReppas/On_visual_explanation_of_supervised_and_self-supervised_learning

Visualization methods to interpret CNNs and Vision Transformers, trained in a supervised or self-supervised way. The methods are based on CAM or on the attention mechanism of Transformers. The results are evaluated qualitatively and quantitatively.

Language: Python - Size: 14.5 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

WanyuGroup/CVPR2022-OrphicX

Official code for the CVPR 2022 (oral) paper "OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks."

Language: Python - Size: 1.94 MB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 23 - Forks: 10

VictorNico/NNs_from_scratch

Build a Neural net from scratch without keras or pytorch just by using numpy for calculus, pandas for data loading.

Language: Jupyter Notebook - Size: 29.3 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0