OscarcarLi / PrototypeDLLinks
Codebase for "Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains Its Predictions" (to appear in AAAI 2018)
☆76Updated 8 years ago
Alternatives and similar repositories for PrototypeDL
Users that are interested in PrototypeDL are comparing it to the libraries listed below
Sorting:
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆129Updated 4 years ago
- ☆125Updated 4 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆132Updated 5 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆128Updated 4 years ago
- Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)☆62Updated 6 years ago
- ☆135Updated 6 years ago
- Code and data for the experiments in "On Fairness and Calibration"☆51Updated 3 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 3 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆91Updated 5 years ago
- ☆14Updated last year
- GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model’s Prediction. Thai Le, Suhang Wang, Dongwon …☆21Updated 4 years ago
- Implementation of the paper "Shapley Explanation Networks"☆88Updated 4 years ago
- Code for AAAI 2018 accepted paper: "Beyond Sparsity: Tree Regularization of Deep Models for Interpretability"☆79Updated 7 years ago
- ☆63Updated 5 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 5 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 4 years ago
- ☆50Updated 2 years ago
- ☆65Updated last year
- Code for "Generative causal explanations of black-box classifiers"☆35Updated 4 years ago
- Gold Loss Correction☆88Updated 7 years ago
- Tools for training explainable models using attribution priors.☆125Updated 4 years ago
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 4 years ago
- Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.☆175Updated 2 years ago
- Explaining Image Classifiers by Counterfactual Generation☆28Updated 3 years ago
- Code for paper EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE☆42Updated 2 years ago
- Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"☆31Updated 2 years ago
- Deep Neural Decision Trees☆163Updated 3 years ago
- ☆43Updated 7 years ago
- Codes for reproducing the contrastive explanation in “Explanations based on the Missing: Towards Contrastive Explanations with Pertinent…☆54Updated 7 years ago
- Self-Explaining Neural Networks☆13Updated 2 years ago