flaviovdf / label-shiftLinks
☆32Updated 4 years ago
Alternatives and similar repositories for label-shift
Users that are interested in label-shift are comparing it to the libraries listed below
Sorting:
- A simple algorithm to identify and correct for label shift.☆22Updated 7 years ago
- Active and Sample-Efficient Model Evaluation☆26Updated 6 months ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆129Updated 4 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
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆132Updated 5 years ago
- Implementation of the paper "Shapley Explanation Networks"☆89Updated 4 years ago
- Code repository for our paper "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift": https://arxiv.org/abs/1810.119…☆107Updated last year
- Label shift experiments☆17Updated 5 years ago
- ☆30Updated 7 years ago
- Codebase for "Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains Its Predictions" (to appear in AA…☆76Updated 8 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆151Updated 3 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 5 years ago
- ☆38Updated 5 years ago
- Code and results accompanying our paper titled Mixture Proportion Estimation and PU Learning: A Modern Approach at Neurips 2021 (Spotligh…☆44Updated last year
- Calibration of Convolutional Neural Networks☆170Updated 2 years ago
- This repository contains the code used in a publication 'Active Learning for Decision-Making from Imbalanced Observational Data', Iiris S…☆11Updated 6 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 2 years ago
- Reusable BatchBALD implementation☆79Updated last year
- ☆26Updated 5 years ago
- Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".☆30Updated 4 years ago
- (ICML 2021) Mandoline: Model Evaluation under Distribution Shift☆30Updated 4 years ago
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 4 years ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated last year
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆161Updated last year
- ☆31Updated 4 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 4 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 4 years ago
- Official PyTorch implementation of "Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error"☆37Updated 2 years ago
- [ICML2020] "Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training" by Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gon…☆69Updated 3 years ago
- Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.☆175Updated 2 years ago