inouye-lab / ShapleyExplanationNetworksLinks
Implementation of the paper "Shapley Explanation Networks"
☆88Updated 5 years ago
Alternatives and similar repositories for ShapleyExplanationNetworks
Users that are interested in ShapleyExplanationNetworks are comparing it to the libraries listed below
Sorting:
- ☆41Updated 2 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
- [NeurIPS’20] ⚖️ Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. | 设计元知识驱动的采样器解决类别不平衡问题☆111Updated last year
- Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.☆175Updated 2 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆132Updated 5 years ago
- Local explanations with uncertainty 💐!☆42Updated 2 years ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated last year
- Self-Explaining Neural Networks☆43Updated 5 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆116Updated 5 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆129Updated 4 years ago
- Tilted Empirical Risk Minimization (ICLR '21)☆60Updated 2 years ago
- ☆31Updated 4 years ago
- Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)☆62Updated 6 years ago
- Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution …☆77Updated 3 years ago
- Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".☆30Updated 4 years ago
- An amortized approach for calculating local Shapley value explanations☆105Updated 2 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆53Updated 4 years ago
- demonstration of the information bottleneck theory for deep learning☆68Updated 8 years ago
- ☆32Updated 7 years ago
- Implementation of the paper "Understanding anomaly detection with deep invertible networks through hierarchies of distributions and featu…☆43Updated 5 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 4 years ago
- Self-Explaining Neural Networks☆13Updated 2 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆58Updated 7 years ago
- A Pytorch implementation of missing data imputation using optimal transport.☆105Updated 4 years ago
- [ICML2020] "Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training" by Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gon…☆69Updated 4 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆51Updated 4 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆50Updated 4 years ago
- Introduction, selected papers and possible corresponding codes in our review paper "A Survey of Neural Trees"☆85Updated 3 years ago
- Code for "Generative causal explanations of black-box classifiers"☆35Updated 5 years ago
- Pytorch Implementation of the Nonlinear Information Bottleneck☆41Updated last year