Jianbo-Lab / L2X
☆124Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for L2X
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆125Updated 3 years ago
- Codebase for "Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains Its Predictions" (to appear in AA…☆73Updated 7 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆129Updated 4 years ago
- Supervised Local Modeling for Interpretability☆28Updated 6 years ago
- ☆131Updated 5 years ago
- Code and data for the experiments in "On Fairness and Calibration"☆50Updated 2 years ago
- A lightweight implementation of removal-based explanations for ML models.☆57Updated 3 years ago
- Tools for training explainable models using attribution priors.☆121Updated 3 years ago
- Algorithms for abstention, calibration and domain adaptation to label shift.☆36Updated 4 years ago
- Experiments for AAAI anchor paper☆61Updated 6 years ago
- To Trust Or Not To Trust A Classifier. A measure of uncertainty for any trained (possibly black-box) classifier which is more effective t…☆173Updated last year
- Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)☆60Updated 5 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆127Updated 3 years ago
- This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.☆117Updated 3 years ago
- Code for AAAI 2018 accepted paper: "Beyond Sparsity: Tree Regularization of Deep Models for Interpretability"☆78Updated 6 years ago
- Code repository for our paper "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift": https://arxiv.org/abs/1810.119…☆102Updated 7 months ago
- Feature Interaction Interpretability via Interaction Detection☆34Updated last year
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 2 years ago
- Code for paper EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE☆37Updated last year
- Model Agnostic Counterfactual Explanations☆87Updated 2 years ago
- Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"☆98Updated 5 years ago
- GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model’s Prediction. Thai Le, Suhang Wang, Dongwon …☆22Updated 3 years ago
- Code/figures in Right for the Right Reasons☆55Updated 3 years ago
- ☆50Updated last year
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆101Updated 4 years ago
- Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.☆40Updated 2 years ago
- Python code for training fair logistic regression classifiers.☆189Updated 2 years ago
- Fair Empirical Risk Minimization (FERM)☆37Updated 4 years ago
- Testing Nerual Tangent Kernel (NTK) on small UCI datasets☆82Updated 5 years ago
- code release for Representer point Selection for Explaining Deep Neural Network in NeurIPS 2018☆67Updated 3 years ago