CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
☆304Oct 2, 2023Updated 2 years ago
Alternatives and similar repositories for CARLA
Users that are interested in CARLA are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- A collection of algorithms of counterfactual explanations.☆53Mar 22, 2021Updated 5 years ago
- Model Agnostic Counterfactual Explanations☆91Sep 30, 2022Updated 3 years ago
- Implementation of the paper titled: "FACE: Feasible and actionable counterfactual recourse" by Rafael et. at. - https://arxiv.org/pdf/190…☆14Dec 12, 2020Updated 5 years ago
- Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"☆31Mar 24, 2023Updated 3 years ago
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,520Jul 13, 2025Updated last year
- Simple, predictable pricing with DigitalOcean hosting • AdAlways know what you'll pay with monthly caps and flat pricing. Enterprise-grade infrastructure trusted by 600k+ customers.
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆38Dec 27, 2022Updated 3 years ago
- python tools to check recourse in linear classification☆77Jan 8, 2021Updated 5 years ago
- Easiest way to generate counterfactual explanations☆12Sep 26, 2023Updated 2 years ago
- Generate robust counterfactual explanations for machine learning models☆18Jun 8, 2023Updated 3 years ago
- Source Code of the ROAD benchmark for feature attribution methods (ICML22)☆25Jun 26, 2023Updated 3 years ago
- Gaussian Membership Inference Privacy (NeurIPS 2023)☆12Jul 27, 2024Updated 2 years ago
- A modular Python framework for standardized evaluation and benchmarking of online learning models.☆10Nov 24, 2022Updated 3 years ago
- Glacier: Guided Locally Constrained Counterfactual Explanations for Time Series Classification (Machine Learning journal)☆12Mar 15, 2024Updated 2 years ago
- Algorithms for explaining machine learning models☆2,640Oct 17, 2025Updated 9 months ago
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Minimal template for a Python library project☆11Nov 21, 2022Updated 3 years ago
- ☆11Apr 5, 2023Updated 3 years ago
- OmniXAI: A Library for eXplainable AI☆970Jun 2, 2026Updated last month
- Repository of the paper "Imperceptible Adversarial Attacks on Tabular Data" presented at NeurIPS 2019 Workshop on Robust AI in Financial …☆16Nov 9, 2021Updated 4 years ago
- [JMLR 2023] Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆672May 4, 2026Updated 2 months ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆35Apr 23, 2024Updated 2 years ago
- Repository for Deep Structural Causal Models for Tractable Counterfactual Inference☆298Jul 6, 2023Updated 3 years ago
- Multi-Objective Counterfactuals☆43Jul 8, 2022Updated 4 years ago
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆257Aug 17, 2024Updated last year
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- A collection of research materials on explainable AI/ML☆1,650Mar 7, 2026Updated 4 months ago
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,601Updated this week
- Interpretability and explainability of data and machine learning models☆1,791Updated this week
- A Python library that helps data scientists to infer causation rather than observing correlation.☆2,477Jun 29, 2026Updated last month
- Modular Python Toolbox for Fairness, Accountability and Transparency Forensics☆79Apr 13, 2026Updated 3 months ago
- DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a uni…☆8,236Updated this week
- Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …☆52Jan 7, 2021Updated 5 years ago
- Datasets derived from US census data☆290May 15, 2024Updated 2 years ago
- Tools for robustness evaluation in interpretability methods☆10Jun 25, 2021Updated 5 years ago
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- A unified framework for Deep Learning Models on tabular data☆1,677Apr 17, 2026Updated 3 months ago
- A Python package for causal inference in quasi-experimental settings☆1,163Updated this week
- Strategies to deploy deep learning models☆27Jul 18, 2018Updated 8 years ago
- CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox☆47Jul 17, 2026Updated last week
- Irregular time series made easy☆23Mar 23, 2026Updated 4 months ago
- [ICML 24] A novel automated neuron explanation framework that can accurately describe poly-semantic concepts in deep neural networks☆14May 2, 2025Updated last year
- Flexible Mixed Integer Evolutionary Strategies☆16Mar 19, 2025Updated last year