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1. Trustworthy-ML-Lab/Label-free-CBM Trustworthy-ML-Lab/Label-free-CBM Public

   [ICLR 23] A new framework to transform any neural networks into an interpretable concept-bottleneck-model (CBM) without needing labeled concept data

   Jupyter Notebook 109 23

2. train_mnist_fast train_mnist_fast Public

   How to train a CNN to 99% accuracy on MNIST in less than a second on a laptop

   Jupyter Notebook 68 11

3. Trustworthy-ML-Lab/CLIP-dissect Trustworthy-ML-Lab/CLIP-dissect Public

   [ICLR 23 spotlight] An automatic and efficient tool to describe functionalities of individual neurons in DNNs

   Jupyter Notebook 55 16

4. radial_rl_v2 radial_rl_v2 Public

   This repository contains the official code for our NeurIPS 2021 publication "Robust Deep Reinforcement Learning through Adversarial Loss​"

   Python 30 6

5. Trustworthy-ML-Lab/Linear-Explanations Trustworthy-ML-Lab/Linear-Explanations Public

   [ICML 24] A novel automated neuron explanation framework that can accurately describe poly-semantic concepts in deep neural networks

   Jupyter Notebook 13

6. Trustworthy-ML-Lab/Neuron_Eval Trustworthy-ML-Lab/Neuron_Eval Public

   [ICML 25] A unified mathematical framework to evaluate neuron explanations of deep learning models with sanity tests

   Jupyter Notebook 6