suinleelab / attributionpriorsLinks
Tools for training explainable models using attribution priors.
☆124Updated 4 years ago
Alternatives and similar repositories for attributionpriors
Users that are interested in attributionpriors are comparing it to the libraries listed below
Sorting:
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆128Updated 4 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆129Updated 3 years ago
- A lightweight implementation of removal-based explanations for ML models.☆58Updated 4 years ago
- A repository for explaining feature attributions and feature interactions in deep neural networks.☆188Updated 3 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆150Updated 2 years ago
- ☆124Updated 4 years ago
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 3 years ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆42Updated 2 years ago
- Multislice PHATE for tensor embeddings☆60Updated 4 years ago
- Code/figures in Right for the Right Reasons☆55Updated 4 years ago
- Codebase for Learning Invariances in Neural Networks☆95Updated 2 years ago
- Code repository for our paper "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift": https://arxiv.org/abs/1810.119…☆105Updated last year
- ☆134Updated 5 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆131Updated 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
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Updated 6 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆92Updated 4 years ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Updated 2 years ago
- Combating hidden stratification with GEORGE☆64Updated 4 years ago
- ☆100Updated 3 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated last year
- Uncertainty in Conditional Average Treatment Effect Estimation☆33Updated 4 years ago
- Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR☆62Updated 5 years ago
- Reusable BatchBALD implementation☆79Updated last year
- ☆14Updated last year
- Codes for reproducing the contrastive explanation in “Explanations based on the Missing: Towards Contrastive Explanations with Pertinent…☆54Updated 7 years ago
- Algorithms for abstention, calibration and domain adaptation to label shift.☆37Updated 4 years ago
- Code for "Neural causal learning from unknown interventions"☆104Updated 5 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