vios-s / Diff-SCMLinks
Code for Diff-SCM paper
☆101Updated 2 years ago
Alternatives and similar repositories for Diff-SCM
Users that are interested in Diff-SCM are comparing it to the libraries listed below
Sorting:
- (ICML 2023) High Fidelity Image Counterfactuals with Probabilistic Causal Models☆67Updated 9 months ago
- Benchmark study of quality and faithfulness of counterfactual image generation☆30Updated 8 months ago
- Diffusion Models for Causal Discovery☆90Updated 2 years ago
- Repository for our NeurIPS 2022 paper "Concept Embedding Models", our NeurIPS 2023 paper "Learning to Receive Help", and our ICML 2025 pa…☆72Updated last week
- VAEs and nonlinear ICA: a unifying framework☆50Updated 6 years ago
- InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models☆35Updated 10 months ago
- Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with…☆59Updated 2 years ago
- Official PyTorch implementation for the paper "CARD: Classification and Regression Diffusion Models"☆234Updated 2 years ago
- ☆30Updated 9 months ago
- Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations is a ServiceNow Research project that was started at Elemen…☆13Updated 2 years ago
- Official PyTorch code for "Out-of-distribution detection with denoising diffusion models"☆51Updated last year
- ☆44Updated last year
- This repository summarizes the material gathered for the tutorial on learning disentangled representations in the imaging domain, and ser…☆62Updated 3 years ago
- Repository for Deep Structural Causal Models for Tractable Counterfactual Inference☆293Updated 2 years ago
- ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping☆54Updated 3 years ago
- [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift☆111Updated 2 years ago
- Official codebase for the paper "Provable concept learning for interpretable predictions using variational inference".☆14Updated 3 years ago
- ☆24Updated last year
- Experiments to reproduce results in Interventional Causal Representation Learning.☆28Updated 2 years ago
- counterfactuals for magnetic resonance images of multiple sclerosis☆26Updated 4 years ago
- Modular and intuitive Hypernetworks in Pytorch☆40Updated 2 years ago
- Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style☆54Updated 4 years ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆33Updated 4 years ago
- ☆20Updated 4 years ago
- Disentangled gEnerative cAusal Representation (DEAR)☆66Updated 3 years ago
- 🧶 Modular VAE disentanglement framework for python built with PyTorch Lightning ▸ Including metrics and datasets ▸ With strongly supervi…☆132Updated 2 years ago
- Quantile risk minimization☆25Updated last year
- Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning (http://jmlr.org/papers/v20/19-033.html)☆91Updated 11 months ago
- GAN-based method to create counterfactual explanations for chest X-rays☆25Updated 2 months ago
- Official source code repository for the ICML 2021 paper "Hierarchical VAEs Know What They Don't Know"☆31Updated 4 years ago