There are 5 repositories under structure-learning topic.
A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization"
[Experimental] Global causal discovery algorithms
A Snakemake workflow to run and benchmark structure learning (a.k.a. causal discovery) algorithms for probabilistic graphical models.
Document Image Classification with Intra-Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks
[AAAI 2020 Oral] Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution
Sum-Product Network learning routines in python
Bayesian network structure learning
Source code for the paper "Causal Modeling of Twitter Activity during COVID-19". Computation, 2020.
Experiments on structure learning of Bayesian Networks with emphasis on finding causal relationship
The source code repository for the FactorBase system
Tractable learning of Bayesian networks from partially observed data
Code accompanying paper "Model-Augmented Conditional Mutual Information Estimation for Feature Selection" in UAI 2020
A curated list of causal structure learning research papers with implementations.
This is the official implementation of the bipartite matching experiment from the paper "Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization".
Python implementation of Bayesian Network Structure Learning using Quantum Annealing https://doi.org/10.1140/epjst/e2015-02349-9
GGM structure learning using 1 bit.
Structure Learning of Gradual Bipolar Argumentation Graphs using Genetic Algorithms
Quasi-determinism screening for fast Bayesian Network Structure Learning (from T.Rahier's PhD thesis, 2018)
bnlearn
Bayesian network analysis in R
Bayesian Network structure learning with encoding into a Quadratic Unconstrained Binary Optimisation (QUBO) problem.