suinleelab / path_explainLinks
A repository for explaining feature attributions and feature interactions in deep neural networks.
β188Updated 3 years ago
Alternatives and similar repositories for path_explain
Users that are interested in path_explain are comparing it to the libraries listed below
Sorting:
- Tools for training explainable models using attribution priors.β124Updated 4 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" π§ (ICLR 2019)β129Updated 3 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" htβ¦β128Updated 4 years ago
- Code repository for our paper "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift": https://arxiv.org/abs/1810.119β¦β105Updated last year
- A lightweight implementation of removal-based explanations for ML models.β58Updated 4 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotligβ¦β150Updated 2 years ago
- Enabling easy statistical significance testing for deep neural networks.β336Updated last year
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.β131Updated 4 years ago
- β264Updated 5 years ago
- Official Code Repo for the Paper: "How does This Interaction Affect Me? Interpretable Attribution for Feature Interactions", In NeurIPS 2β¦β39Updated 2 years ago
- Algorithms for abstention, calibration and domain adaptation to label shift.β37Updated 4 years ago
- Multislice PHATE for tensor embeddingsβ60Updated 4 years ago
- Training and evaluating NBM and SPAM for interpretable machine learning.β78Updated 2 years ago
- Reusable BatchBALD implementationβ79Updated last year
- Pytorch implementation of VAEs for heterogeneous likelihoods.β42Updated 2 years ago
- β470Updated 3 months ago
- Combating hidden stratification with GEORGEβ64Updated 4 years ago
- β124Updated 4 years ago
- Python implementation of GLN in different frameworksβ97Updated 4 years ago
- A Machine Learning workflow for Slurm.β150Updated 4 years ago
- Course webpage for COMP 790, (Deep) Learning from Limited Labeled Dataβ304Updated 4 years ago
- Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLRβ62Updated 5 years ago
- Implemented Machine Learning Algorithms in Hyperbolic Geometry (MDS, K-Means, Support vector machines, etc.)β137Updated 5 years ago
- List of relevant resources for machine learning from explanatory supervisionβ159Updated 3 weeks ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true claβ¦β244Updated 2 years ago
- Library that contains implementations of machine learning components in the hyperbolic spaceβ140Updated last year
- Neural Additive Models (Google Research)β71Updated 3 years ago
- Ordinal regression models in PyTorchβ147Updated 3 years ago
- Code for "Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning"β416Updated last year
- Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)β50Updated 5 years ago