rpatrik96 / ima-vae
This is the code for the paper Embrace the Gap: VAEs perform Independent Mechanism Analysis, showing that optimizing the ELBO is equivalent to optimizing the IMA-regularized log-likelihood under certain assumptions (e.g., small decoder variance).
☆23Updated 10 months ago
Alternatives and similar repositories for ima-vae:
Users that are interested in ima-vae are comparing it to the libraries listed below
- ☆23Updated last year
- Code for the paper: "Independent mechanism analysis, a new concept?"☆24Updated last year
- A set of tests for evaluating large-scale algorithms for Wasserstein-1 transport computation (NeurIPS'22).☆20Updated 6 months ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆32Updated 3 years ago
- ☆17Updated last year
- Code for GFlowNet-EM, a novel algorithm for fitting latent variable models with compositional latents and an intractable true posterior.☆41Updated last year
- Code for ICE-BeeM paper - NeurIPS 2020☆86Updated 3 years ago
- ☆24Updated 5 months ago
- [CLeaR23] Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning☆30Updated last year
- Dirichlet-Variational Auto-Encoder by PyTorch☆22Updated last year
- VAEs and nonlinear ICA: a unifying framework☆34Updated 4 years ago
- ☆20Updated 3 years ago
- NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models☆14Updated 4 months ago
- ☆32Updated 9 months ago
- ☆37Updated 7 months ago
- This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (partic…☆17Updated 6 months ago
- Featurized Density Ratio Estimation☆20Updated 3 years ago
- ☆53Updated 7 months ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆82Updated 11 months ago
- DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks☆51Updated last year
- Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", b…☆19Updated last year
- Experiments to reproduce results in Interventional Causal Representation Learning.☆26Updated 2 years ago
- VAEs and nonlinear ICA: a unifying framework☆47Updated 5 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 4 years ago
- GP Sinkhorn Implementation, paper: https://www.mdpi.com/1099-4300/23/9/1134☆22Updated 2 years ago
- ☆15Updated 2 years ago
- Code for "Causal autoregressive flows" - AISTATS, 2021☆44Updated 3 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆44Updated last year
- ☆37Updated 4 years ago
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 3 years ago