gulnazaki / counterfactual-benchmarkLinks
Benchmark study of quality and faithfulness of counterfactual image generation
☆24Updated 4 months ago
Alternatives and similar repositories for counterfactual-benchmark
Users that are interested in counterfactual-benchmark are comparing it to the libraries listed below
Sorting:
- Code for Diff-SCM paper☆97Updated 2 years ago
- Repository for Deep Structural Causal Models for Tractable Counterfactual Inference☆287Updated 2 years ago
- Diffusion Models for Causal Discovery☆85Updated 2 years ago
- (ICML 2023) High Fidelity Image Counterfactuals with Probabilistic Causal Models☆62Updated 5 months ago
- counterfactuals for magnetic resonance images of multiple sclerosis☆26Updated 4 years ago
- Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off" and our NeurIPS 2023 paper…☆66Updated 3 weeks ago
- The repository contains lists of papers on causality and how relevant techniques are being used to further enhance deep learning era comp…☆95Updated 2 years ago
- ☆39Updated last year
- ☆27Updated 4 months ago
- Neural Additive Models (Google Research)☆71Updated 3 years ago
- [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift☆108Updated 2 years ago
- Data Augmentation with Variational Autoencoders (TPAMI)☆140Updated 2 years ago
- Experiments to reproduce results in Interventional Causal Representation Learning.☆25Updated 2 years ago
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆67Updated 2 years ago
- Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations is a ServiceNow Research project that was started at Elemen…☆13Updated 2 years ago
- Official Implementation of the paper: "A Rate-Distorion View of Uncertainty Quantification", ICML 2024☆28Updated last year
- Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"☆18Updated 4 years ago
- InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models☆34Updated 5 months ago
- Code for comparison of multimodal VAE models☆29Updated 3 months ago
- Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with…☆57Updated 2 years ago
- Official PyTorch code for "Out-of-distribution detection with denoising diffusion models"☆51Updated last year
- Concept Bottleneck Models, ICML 2020☆210Updated 2 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆85Updated last year
- Code for the paper "Post-hoc Concept Bottleneck Models". Spotlight @ ICLR 2023☆82Updated last year
- [CLeaR23] Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning☆30Updated 2 years ago
- 🧶 Modular VAE disentanglement framework for python built with PyTorch Lightning ▸ Including metrics and datasets ▸ With strongly supervi…☆128Updated 2 years ago
- Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI☆55Updated 3 years ago
- Optimal Transport Dataset Distance☆168Updated 3 years ago
- ☆51Updated last year