CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
☆303Oct 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☆90Sep 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
- Source Code of the ROAD benchmark for feature attribution methods (ICML22)☆25Jun 26, 2023Updated 3 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,519Jul 13, 2025Updated 11 months ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆37Dec 27, 2022Updated 3 years ago
- python tools to check recourse in linear classification☆76Jan 8, 2021Updated 5 years ago
- Generate robust counterfactual explanations for machine learning models☆18Jun 8, 2023Updated 3 years ago
- Gaussian Membership Inference Privacy (NeurIPS 2023)☆12Jul 27, 2024Updated last year
- Algorithms for explaining machine learning models☆2,634Oct 17, 2025Updated 8 months ago
- 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☆969Jun 2, 2026Updated last month
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- For calculating global feature importance using Shapley values.☆292Jun 29, 2026Updated last week
- [JMLR 2023] Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆667May 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
- ☆29Nov 2, 2021Updated 4 years ago
- Multi-Objective Counterfactuals☆43Jul 8, 2022Updated 4 years ago
- A collection of research materials on explainable AI/ML☆1,651Mar 7, 2026Updated 4 months ago
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆255Aug 17, 2024Updated last year
- A Python package for feature selection on a simulated data stream☆10Apr 21, 2022Updated 4 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,596May 26, 2026Updated last month
- A Python library that helps data scientists to infer causation rather than observing correlation.☆2,472Jun 29, 2026Updated last week
- Interpretability and explainability of data and machine learning models☆1,783May 22, 2026Updated last month
- Modular Python Toolbox for Fairness, Accountability and Transparency Forensics☆79Apr 13, 2026Updated 2 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…☆8,202Updated 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
- ☆44May 17, 2020Updated 6 years ago
- Datasets derived from US census data☆289May 15, 2024Updated 2 years ago
- A unified framework for Deep Learning Models on tabular data☆1,675Apr 17, 2026Updated 2 months ago
- 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 Python package for causal inference in quasi-experimental settings☆1,161Updated this week
- CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox☆47Jun 9, 2026Updated 3 weeks ago
- ☆11Oct 22, 2020Updated 5 years ago
- [NeurIPS 2024] CoSy is an automatic evaluation framework for textual explanations of neurons.☆20Jan 28, 2026Updated 5 months ago
- ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Inte…☆4,705Jun 29, 2026Updated last week
- 💡 Adversarial attacks on explanations and how to defend them☆335Nov 30, 2024Updated last year
- Interpretable Explanations of Black Boxes by Meaningful Perturbation Pytorch☆12Aug 30, 2024Updated last year