realityengines / post_hoc_debiasing
☆17Updated 4 years ago
Alternatives and similar repositories for post_hoc_debiasing:
Users that are interested in post_hoc_debiasing are comparing it to the libraries listed below
- (ICML 2021) Mandoline: Model Evaluation under Distribution Shift☆31Updated 3 years ago
- Privacy-Preserving Bandits (MLSys'20)☆22Updated 2 years ago
- Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"☆27Updated 4 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆40Updated 2 years ago
- EMNLP Findings 2020: Reevaluating Adversarial Examples in Natural Language☆7Updated 4 years ago
- Model Patching: Closing the Subgroup Performance Gap with Data Augmentation☆42Updated 4 years ago
- ☆35Updated last year
- Implements EvoNorms B0 and S0 as proposed in Evolving Normalization-Activation Layers.☆11Updated 4 years ago
- Advances in Neural Information Processing Systems (NeurIPS 2021)☆22Updated 2 years ago
- Concealed Data Poisoning Attacks on NLP Models☆21Updated last year
- Hyperparameter tuning via uncertainty modeling☆47Updated 11 months ago
- This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"☆50Updated 3 years ago
- Investigate the speed of adaptation of structural causal models☆16Updated 4 years ago
- Scalable Bayes via Barycenter in Wasserstein Space☆9Updated 7 years ago
- Parameter-Space Saliency Maps for Explainability☆23Updated 2 years ago
- The code reproduces the results of the experiments in the paper. In particular, it performs experiments in which machine-learning models …☆20Updated 3 years ago
- Measuring data importance over ML pipelines using the Shapley value.☆38Updated last month
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆21Updated 2 years ago
- Learning perturbation sets for robust machine learning☆64Updated 3 years ago
- ☆11Updated 5 years ago
- ☆25Updated 4 years ago
- ☆38Updated 3 years ago
- Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction☆35Updated 2 years ago
- Ludwig benchmark☆20Updated 3 years ago
- Code repository for the AISTATS 2021 paper "Towards Understanding the Optimal Behaviors of Deep Active Learning Algorithms"☆15Updated 4 years ago
- An empirical investigation of deep learning theory☆16Updated 5 years ago
- Notebooks for managing NeurIPS 2014 and analysing the NeurIPS experiment.☆11Updated 10 months ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- ModelDiff: A Framework for Comparing Learning Algorithms☆56Updated last year
- Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.☆19Updated 2 years ago