structure-learning

There are 5 repositories under structure-learning topic.

erdogant / bnlearn
Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.
bayesian-inference structure-learning sampling-methods dag directed-acyclic-graph parameter-learning causal-models causality-analysis causal-networks causal machine-learning python
Language:Jupyter Notebook 556
aimclub / BAMT
Repository of a data modeling and analysis tool based on Bayesian networks
bayesian-networks synthetic-data mixed-data structure-learning parameters-learning
Language:Python 133
kevinsbello / dagma
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"
structure-learning causal-discovery graphical-models neurips-2022 bayesian-networks dags
Language:Python 131
py-why / dodiscover
[Experimental] Global causal discovery algorithms
causal-inference causality graphs python structure-learning
Language:Python 109
phlippe / ENCO
Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
causal-discovery pytorch causality structure-learning
Language:Python 86
probsys / AutoGP.jl
Automated Bayesian model discovery for time series data
bayesian-inference forecasting gaussian-process machine-learning structure-learning times-series icml
Language:Julia 83
felixleopoldo / benchpress
Scalable open-source software to run, develop, and benchmark causal discovery algorithms
graphical-models bayesian-networks markov-networks benchmarking reproducible-research snakemake-workflow structure-learning causal-discovery causal-models causality
Language:Python 73
GOLEM
aimclub / GOLEM
Graph Optimiser for Learning and Evolution of Models
dag evolutionary-optimization structure-learning graph-learning ai genetic-programming
Language:Python 70
larslorch / avici
Amortized Inference for Causal Structure Learning, NeurIPS 2022
amortized-inference causal-discovery causal-inference causality structure-learning transformers variational-inference
Language:Python 68
larslorch / dibs
DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021
bayesian-inference bayesian-networks variational-inference structure-learning causal-inference
Language:Python 51
hiarindam / document-image-classification-TL-SG
Document Image Classification with Intra-Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks
document-classification deep-learning transfer-learning structure-learning deep-convolutional-neural-networks image-classification document-image-classification training-strategies
Language:Python 43
agadetsky / pytorch-pl-variance-reduction
[AAAI 2020 Oral] Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution
aaai2020 pytorch variance-reduction plackett-luce relax rebar structure-learning directed-acyclic-graph control-variates neurips-2019 permutations plackett-luce-distribution
Language:Jupyter Notebook 39
salvaRC / Graphino
Code associated with the paper "The World as a Graph: Improving El Niño Forecasting with Graph Neural Networks".
graph-neural-networks enso deep-learning structure-learning long-range-forecasting el-nino la-nina
Language:Jupyter Notebook 33
arranger1044 / spyn
Sum-Product Network learning routines in python
spn sum-product-networks structure-learning
Language:Python 27
BNSL
Howardhuang98 / BNSL
Bayesian network structure learning
algorithm bayesian-network deep-learning structure-learning
Language:Python 18
microsoft / ML4C
[SDM'23] ML4C: Seeing Causality Through Latent Vicinity
causal causal-discovery causality causality-algorithms discrete graph structure-learning supervised-learning supervised-causal-learning
Language:Python 13
Duntrain / dagrad
dagrad is a Python package that provides an extensible, modular platform for developing and experimenting with differentiable (gradient-based) structure learning methods.
bayesian-networks causal-discovery dags graphical-models structure-learning
Language:Python 11
ogencoglu / causal_twitter_modeling_covid19
Source code for the paper "Causal Modeling of Twitter Activity during COVID-19". Computation, 2020.
causal-inference causality-analysis graph-algorithms social-media twitter covid-19 covid19 structure-learning bayesian-networks sentiment-analysis health-informatics social-media-analysis social-media-mining machine-learning
Language:Jupyter Notebook 10
sfu-cl-lab / FactorBase
The source code repository for the FactorBase system
bayesian-network structure-learning relational-database log-linear-model factor-graphs mysql-database relational-learning big-model markov-logic-network mln relational-dependency-network rdn bayesian-networks relational-databases bif
Language:Java 10
massimo-rizzoli / BNSL-QA-python
Python implementation of Bayesian Network Structure Learning using Quantum Annealing https://doi.org/10.1140/epjst/e2015-02349-9
bayesian-network structure-learning python dwave quantum-annealing
Language:Python 9
QueensGambit / PGM-Causal-Reasoning
Experiments on structure learning of Bayesian Networks with emphasis on finding causal relationship
bayesian-networks structure-learning probabilistic-graphical-models
Language:Jupyter Notebook 9
Duntrain / TOPO
Optimizing NOTEARS Objectives via Topological Swaps
causal-discovery graphical-models icml-2023 structure-learning
Language:Python 8
furrer-lab / abn
Bayesian network analysis in R
bayesian-network binomial categorical-data gaussian grouped-datasets mixed-effects multinomial multivariate poisson structure-learning
Language:R 8
syanga / dglearn
Python implementation of "Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs," in ICML 2020
bayesian-network structure-learning
Language:Python 8
sergioluengosanchez / TSEM
Tractable learning of Bayesian networks from partially observed data
structural-expectation-maximization bayesian-network incomplete-data inference-complexity structure-learning
Language:Python 7
syanga / model-augmented-mutual-information
Code accompanying paper "Model-Augmented Conditional Mutual Information Estimation for Feature Selection" in UAI 2020
feature-selection markov-blanket mutual-information structure-learning
Language:Jupyter Notebook 6
fritzbayer / Causal-Discovery-Research-Papers
A curated list of causal structure learning research papers with implementations.
bayesian-network bayesian-networks causal-discovery causality dag structure-learning causal-inference
5
HeddaCohenIndelman / PerturbedStructuredPredictorsDirect
This is the official implementation of the bipartite matching experiment from the paper "Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization".
structure-learning prediction-problem bipartite-matching icml2021
Language:Python 5
montilab / shine
Structure Learning for Hierarchical Networks
graphical-modeling networks-biology structure-learning
Language:R 5
werkaaa / iscm
Standardizing Structural Causal Models, ICLR 2025
benchmarking causal-discovery causality scm structure-learning
Language:Jupyter Notebook 5
jspieler / QBAF-Learning
Structure Learning of Gradual Bipolar Argumentation Graphs using Genetic Algorithms
abstract-argumentation argumentation-frameworks genetic-algorithm structure-learning
Language:Python 4
miicTeam / miicsearchscore
[ICML 2025] R implementation of MIIC_search&score: a search-and-score algorithm for learning ancestral graphs with latent confounders, using multivariate information over ac-connected subset.
causal-discovery icml-2025 information-theory latent-variables r structure-learning causality confounder graph icml
Language:R 4
tmadeira / ktrees
Computer Science undergraduate thesis: Uniform Generation of k-trees for Learning the Structure of Bayesian Networks (USP 2016).
k-trees bayesian-networks graph-generation structure-learning bounded-treewidth graph-coding sampling
Language:Go 4
python-qds / qdscreen
Quasi-determinism screening for fast Bayesian Network Structure Learning (from T.Rahier's PhD thesis, 2018)
functional-dependency correlation categorical feature-selection bayesian-network structure-learning determinism quasi screening
Language:Python 3
semoglou / ksil
A silhouette-guided instance-weighted k-means algorithm that integrates silhouette scores into the clustering process to improve clustering quality.
clustering clustering-algorithm k-means silhouette k-means-clustering sampling unsupervised-learning weighted-clustering-algorithm centroid-based-clustering instance-weighting partitioning pattern-detection pattern-discovery silhouette-analysis data-segmentation silhouette-score structure-learning data-clustering
Language:Jupyter Notebook 3
VishnuBeji / BayesianNet_QuantumAnnealing
Bayesian Network structure learning with encoding into a Quadratic Unconstrained Binary Optimisation (QUBO) problem.
bayesian-network quantum-annealing structure-learning
Language:Python 3

structure-learning

erdogant / bnlearn

aimclub / BAMT

kevinsbello / dagma

py-why / dodiscover

phlippe / ENCO

probsys / AutoGP.jl

felixleopoldo / benchpress

aimclub / GOLEM

larslorch / avici

larslorch / dibs

hiarindam / document-image-classification-TL-SG

agadetsky / pytorch-pl-variance-reduction

salvaRC / Graphino

arranger1044 / spyn

Howardhuang98 / BNSL

microsoft / ML4C

Duntrain / dagrad

ogencoglu / causal_twitter_modeling_covid19

sfu-cl-lab / FactorBase

massimo-rizzoli / BNSL-QA-python

QueensGambit / PGM-Causal-Reasoning

Duntrain / TOPO

furrer-lab / abn

syanga / dglearn

sergioluengosanchez / TSEM

syanga / model-augmented-mutual-information

fritzbayer / Causal-Discovery-Research-Papers

HeddaCohenIndelman / PerturbedStructuredPredictorsDirect

montilab / shine

werkaaa / iscm

jspieler / QBAF-Learning

miicTeam / miicsearchscore

tmadeira / ktrees

python-qds / qdscreen

semoglou / ksil

VishnuBeji / BayesianNet_QuantumAnnealing