google / TrustScoreLinks
To Trust Or Not To Trust A Classifier. A measure of uncertainty for any trained (possibly black-box) classifier which is more effective than the classifier's own implied confidence (e.g. softmax probability for a neural network).
☆175Updated 2 years ago
Alternatives and similar repositories for TrustScore
Users that are interested in TrustScore are comparing it to the libraries listed below
Sorting:
- ☆134Updated 5 years ago
- ☆125Updated 4 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆128Updated 3 years ago
- Codebase for "Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains Its Predictions" (to appear in AA…☆75Updated 7 years ago
- Algorithms for abstention, calibration and domain adaptation to label shift.☆36Updated 4 years ago
- Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)☆61Updated 5 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆127Updated 4 years ago
- OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)☆62Updated last year
- This is a benchmark to evaluate machine learning local explanaitons quality generated from any explainer for text and image data☆30Updated 4 years ago
- Tools for training explainable models using attribution priors.☆124Updated 4 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆245Updated 5 years ago
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆61Updated 7 years ago
- Python codes for weakly-supervised learning☆123Updated 5 years ago
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 3 years ago
- Code and data for the experiments in "On Fairness and Calibration"☆51Updated 3 years ago
- ☆51Updated 4 years ago
- Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University☆45Updated 2 years ago
- Outlier Exposure with Confidence Control for Out-of-Distribution Detection☆69Updated 4 years ago
- This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.☆117Updated 4 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 2 years ago
- Code/figures in Right for the Right Reasons☆55Updated 4 years ago
- Experiments for AAAI anchor paper☆63Updated 7 years ago
- Code for "Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?"☆45Updated last year
- Code repository for our paper "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift": https://arxiv.org/abs/1810.119…☆104Updated last year
- Gold Loss Correction☆87Updated 6 years ago
- ☆264Updated 5 years ago
- This is a public collection of papers related to machine learning model interpretability.☆26Updated 3 years ago
- GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model’s Prediction. Thai Le, Suhang Wang, Dongwon …☆21Updated 4 years ago
- Modular Python Toolbox for Fairness, Accountability and Transparency Forensics☆77Updated last year
- code release for Representer point Selection for Explaining Deep Neural Network in NeurIPS 2018☆67Updated 3 years ago