Jianbo-Lab / L2X
β124Updated 3 years ago
Alternatives and similar repositories for L2X:
Users that are interested in L2X are comparing it to the libraries listed below
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.β130Updated 4 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" π§ (ICLR 2019)β128Updated 3 years ago
- Tools for training explainable models using attribution priors.β120Updated 3 years ago
- Codebase for "Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains Its Predictions" (to appear in AAβ¦β73Updated 7 years ago
- Supervised Local Modeling for Interpretabilityβ28Updated 6 years ago
- β132Updated 5 years ago
- A lightweight implementation of removal-based explanations for ML models.β57Updated 3 years ago
- Code and data for the experiments in "On Fairness and Calibration"β50Updated 2 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" htβ¦β128Updated 3 years ago
- Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)β60Updated 5 years ago
- Deep Neural Decision Treesβ161Updated 2 years ago
- Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks [NeurIPS 2019]β50Updated 4 years ago
- Model Agnostic Counterfactual Explanationsβ87Updated 2 years ago
- Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLRβ60Updated 4 years ago
- [ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examplesβ67Updated 2 years ago
- Detecting Statistical Interactions from Neural Network Weightsβ47Updated 4 years ago
- Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.β40Updated 3 years ago
- Algorithms for abstention, calibration and domain adaptation to label shift.β36Updated 4 years ago
- Experiments for AAAI anchor paperβ62Updated 6 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.β51Updated 3 years ago
- Feature Interaction Interpretability via Interaction Detectionβ34Updated last year
- Code/figures in Right for the Right Reasonsβ55Updated 4 years ago
- Code for AAAI 2018 accepted paper: "Beyond Sparsity: Tree Regularization of Deep Models for Interpretability"β79Updated 7 years ago
- Testing Nerual Tangent Kernel (NTK) on small UCI datasetsβ83Updated 5 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approachβ46Updated 2 years ago
- code release for Representer point Selection for Explaining Deep Neural Network in NeurIPS 2018β67Updated 3 years ago
- Fair Empirical Risk Minimization (FERM)β37Updated 4 years ago
- GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Modelβs Prediction. Thai Le, Suhang Wang, Dongwon β¦β21Updated 4 years ago
- β42Updated 6 years ago
- Reliability diagrams, Platt's scaling, isotonic regressionβ75Updated 10 years ago