rpatrik96 / nl-causal-representationsLinks
This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (particularly, with Nonlinear ICA) can be used to extract the causal graph from an underlying structural equation model (SEM).
☆18Updated last year
Alternatives and similar repositories for nl-causal-representations
Users that are interested in nl-causal-representations are comparing it to the libraries listed below
Sorting:
- This is the code for the paper Embrace the Gap: VAEs perform Independent Mechanism Analysis, showing that optimizing the ELBO is equivale…☆23Updated last year
- ☆16Updated last year
- ☆11Updated last month
- Hyperbolic PCA via Horospherical Projections☆73Updated 2 years ago
- DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks☆56Updated 3 weeks ago
- ☆25Updated last year
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆86Updated last year
- VAEs and nonlinear ICA: a unifying framework☆38Updated 5 years ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆68Updated 8 months ago
- ☆29Updated 2 years ago
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 3 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- Code to reproduce the numerical experiments in the paper Domain adaptation under structural causal models by Yuansi Chen and Peter Bühlma…☆18Updated 4 years ago
- Mixture of Gaussian Processes Model for Sparse Longitudinal Data☆38Updated 2 years ago
- Python package for the creation, manipulation, and learning of Causal DAGs☆154Updated 2 years ago
- Contrastive neighbor embeddings☆55Updated last month
- Code to reproduce the paper "Do causal predictors generalize better to new domains?"☆12Updated 8 months ago
- A Python package for intrinsic dimension estimation☆93Updated 3 weeks ago
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆90Updated 3 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆85Updated last year
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Updated 2 years ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆42Updated 2 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆45Updated 2 years ago
- ☆37Updated 5 years ago
- ☆12Updated 2 years ago
- Tensorflow implementation for the SVGP-VAE model.☆22Updated 4 years ago
- Causal Modeling with Stationary Diffusions, AISTATS 2024☆19Updated 7 months ago
- Graph matching and clustering by comparing heat kernels via optimal transport.☆27Updated 2 years ago
- GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021☆52Updated 3 years ago
- ☆18Updated last year