lethaiq / GRACE_KDD20Links
GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model’s Prediction. Thai Le, Suhang Wang, Dongwon Lee. 26th ACM SIGKDD Int’l Conf. on Knowledge Discovery and Data Mining (KDD)
☆21Updated 4 years ago
Alternatives and similar repositories for GRACE_KDD20
Users that are interested in GRACE_KDD20 are comparing it to the libraries listed below
Sorting:
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆128Updated 3 years ago
- Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)☆42Updated 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
- ☆124Updated 4 years ago
- Feature Interaction Interpretability via Interaction Detection☆34Updated 2 years ago
- Bringing node2vec and word2vec together for cool stuff☆22Updated 5 years ago
- Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"☆31Updated 2 years ago
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 3 years ago
- ☆34Updated 5 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 5 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆131Updated 4 years ago
- Code for "Generative causal explanations of black-box classifiers"☆34Updated 4 years ago
- Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)☆50Updated 5 years ago
- PyTorch implementation for the paper Classification from Positive, Unlabeled and Biased Negative Data.☆19Updated last year
- Implementation of experiments in paper "Learning from Rules Generalizing Labeled Exemplars" to appear in ICLR2020 (https://openreview.net…☆50Updated 2 years ago
- This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help …☆24Updated 2 years ago
- ☆40Updated 6 years ago
- Code and data for the experiments in "On Fairness and Calibration"☆51Updated 3 years ago
- ☆16Updated 5 years ago
- ☆42Updated 2 years ago
- Implementation of the paper "Shapley Explanation Networks"☆88Updated 4 years ago
- Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR☆62Updated 5 years ago
- 🤖🤖 Attentive Mixtures of Experts (AMEs) are neural network models that learn to output both accurate predictions and estimates of featu…☆42Updated 2 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆41Updated 2 years ago
- Adversarial learning by utilizing model interpretation☆10Updated 6 years ago
- ☆29Updated 6 years ago
- Code implementation of paper Towards A Deep and Unified Understanding of Deep Neural Models in NLP☆73Updated 6 years ago
- MPVAE: Multivariate Probit Variational AutoEncoder for Multi-Label Classification☆31Updated 9 months ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- Code accompanying our paper at AISTATS 2020☆21Updated 4 years ago