Liao-Xu / DDRLinks
This repository is the demo implementation of [Deep Dimension Reduction for Supervised Representation Learning].
☆10Updated 11 months ago
Alternatives and similar repositories for DDR
Users that are interested in DDR are comparing it to the libraries listed below
Sorting:
- A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…☆124Updated last year
- Reinforcement Learning Short Course☆76Updated last week
- Recommender systems in Python☆28Updated 7 months ago
- Code for the paper "Causal Transformer for Estimating Counterfactual Outcomes"☆153Updated last year
- A curated list of awesome variational inference☆26Updated 5 years ago
- ☆45Updated 6 years ago
- Repository for "Differentiable Causal Discovery from Interventional Data"☆76Updated 3 years ago
- VAEs and nonlinear ICA: a unifying framework☆37Updated 5 years ago
- VAEs and nonlinear ICA: a unifying framework☆47Updated 6 years ago
- A meta repository pointing to the other repositories where the implementation of the supplementary examples for our tutorial "Hands-on Ba…☆134Updated 3 years ago
- Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)☆49Updated 6 years ago
- Machine Learning and Artificial Intelligence for Medicine.☆454Updated 2 years ago
- PyTorch implementation of bayesian neural network [torchbnn]☆539Updated last year
- Density Ratio Estimation via Infinitesimal Classification (AISTATS 2022 Oral)☆20Updated 3 years ago
- ☆12Updated last year
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- A PyTorch Implementation of VaDE(https://arxiv.org/pdf/1611.05148.pdf)☆39Updated 4 years ago
- Code accompanying the paper "Empirical analysis of model selection for heterogeneous causal effect estimation"☆13Updated 7 months ago
- Roundtrip: density estimation with deep generative neural networks☆63Updated last year
- On the Role of Sparsity and DAG Constraints for Learning Linear DAGs☆33Updated 4 years ago
- ☆96Updated 2 years ago
- DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021☆51Updated last year
- The Randomized Conditional Independence Test (RCIT) and the Randomized conditional Correlation Test (RCoT)☆25Updated 6 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆143Updated last year
- Python code of Hilbert-Schmidt Independence Criterion☆87Updated 3 years ago
- Solution and Useful Links☆59Updated 3 years ago
- Regression datasets from the UCI repository with standardized test-train splits.☆47Updated 3 years ago
- Experiments for understanding disentanglement in VAE latent representations☆825Updated 2 years ago
- Repository for Deep Structural Causal Models for Tractable Counterfactual Inference☆287Updated 2 years ago
- code for paper: Identifiability Guarantees for Causal Disentanglement from Soft Interventions☆16Updated last year