uhlerlab / actlearn_optintLinks
Active learning for optimal intervention design in causal models
☆16Updated 2 years ago
Alternatives and similar repositories for actlearn_optint
Users that are interested in actlearn_optint are comparing it to the libraries listed below
Sorting:
- code for paper: Identifiability Guarantees for Causal Disentanglement from Soft Interventions☆15Updated 2 years ago
- Python package for the creation, manipulation, and learning of Causal DAGs☆155Updated 2 years ago
- ☆55Updated 6 months ago
- ☆31Updated 3 years ago
- Starter repository for submissions to the CausalBench challenge for gene-gene graph inference from genetic perturbation experiments.☆32Updated 2 years ago
- Supervised Training of Conditional Monge Maps☆19Updated 2 years ago
- ☆11Updated 3 months ago
- ☆63Updated 2 years ago
- Knockoffs for controlled variable selection☆40Updated 5 months ago
- Stable Differentiable Causal Discovery (SDCD)☆24Updated last year
- Paper collection for single cell foundation models☆35Updated last year
- Learning Single-Cell Perturbation Responses using Neural Optimal Transport☆151Updated last year
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆45Updated 2 years ago
- VAEs and nonlinear ICA: a unifying framework☆39Updated 5 years ago
- Repository for "Differentiable Causal Discovery from Interventional Data"☆77Updated 3 years ago
- DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks☆58Updated 2 months ago
- DGCIT: Double Generative Adversarial Networks for Conditional Independence Testing☆11Updated 2 years ago
- Conditional Independence Testing with Generative Adversarial Networks☆14Updated 6 years ago
- Exploring the space of drug combinations to discover synergistic drugs using Active Learning☆24Updated last year
- Scalable python GPU solvers for fused unbalanced gromov-wasserstein optimal transport problems, with routines and examples to align brain…☆46Updated 5 months ago
- Deep Large-Scale Inference UsingKnockoffs☆11Updated 4 years ago
- A probabilistic model to cluster survival data in a variational deep clustering setting☆30Updated 3 years ago
- ☆80Updated 3 years ago
- This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (partic…☆21Updated last year
- GENOT: Generative Neural Optimal Transport☆14Updated 11 months ago
- ☆18Updated last year
- ☆28Updated 3 years ago
- Tensorflow implementation for the SVGP-VAE model.☆22Updated 4 years ago
- Code for the paper "Deep Cox Mixtures for Survival Regression", Machine Learning for Healthcare Conference 2021☆29Updated 3 years ago
- ☆35Updated 2 months ago