Topic: "structure-learning"
pgmpy/pgmpy
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
Language: Python - Size: 12.9 MB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 2,880 - Forks: 736
erdogant/bnlearn
Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.
Language: Jupyter Notebook - Size: 40 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 507 - Forks: 49
aimclub/BAMT
Repository of a data modeling and analysis tool based on Bayesian networks
Language: Python - Size: 106 MB - Last synced at: 20 days ago - Pushed at: 20 days ago - Stars: 126 - Forks: 19
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"
Language: Python - Size: 675 KB - Last synced at: 20 days ago - Pushed at: over 1 year ago - Stars: 115 - Forks: 20
py-why/dodiscover
[Experimental] Global causal discovery algorithms
Language: Python - Size: 522 MB - Last synced at: 18 days ago - Pushed at: about 2 months ago - Stars: 99 - Forks: 17
probsys/AutoGP.jl
Automated Bayesian model discovery for time series data
Language: Julia - Size: 50.6 MB - Last synced at: 7 days ago - Pushed at: 2 months ago - Stars: 72 - Forks: 6
felixleopoldo/benchpress
Scalable open-source software to run, develop, and benchmark causal discovery algorithms
Language: Python - Size: 123 MB - Last synced at: 2 days ago - Pushed at: 3 days ago - Stars: 68 - Forks: 17
aimclub/GOLEM
Graph Optimiser for Learning and Evolution of Models
Language: Python - Size: 22.5 MB - Last synced at: about 19 hours ago - Pushed at: about 20 hours ago - Stars: 64 - Forks: 10
larslorch/avici
Amortized Inference for Causal Structure Learning, NeurIPS 2022
Language: Python - Size: 639 KB - Last synced at: 5 days ago - Pushed at: 3 months ago - Stars: 62 - Forks: 10
phlippe/ENCO
Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
Language: Python - Size: 122 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 54 - Forks: 10
larslorch/dibs
DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021
Language: Python - Size: 13 MB - Last synced at: 16 days ago - Pushed at: about 1 year ago - Stars: 48 - Forks: 11
hiarindam/document-image-classification-TL-SG
Document Image Classification with Intra-Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks
Language: Python - Size: 179 KB - Last synced at: 10 months ago - Pushed at: over 5 years ago - Stars: 42 - Forks: 16
agadetsky/pytorch-pl-variance-reduction
Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution, AAAI 2020 and NeurIPS 2019 Bayesian Deep Learning Workshop
Language: Jupyter Notebook - Size: 410 KB - Last synced at: almost 2 years ago - Pushed at: over 4 years ago - Stars: 35 - Forks: 2
salvaRC/Graphino
Code associated with the paper "The World as a Graph: Improving El Niño Forecasting with Graph Neural Networks". This paper is currently under review.
Language: Jupyter Notebook - Size: 233 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 25 - Forks: 13
arranger1044/spyn
Sum-Product Network learning routines in python
Language: Python - Size: 14.7 MB - Last synced at: about 2 years ago - Pushed at: almost 10 years ago - Stars: 24 - Forks: 4
Howardhuang98/BNSL
Bayesian network structure learning
Language: Python - Size: 7.26 MB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 15 - Forks: 0
microsoft/ML4C
[SDM'23] ML4C: Seeing Causality Through Latent Vicinity
Language: Python - Size: 283 KB - Last synced at: about 23 hours ago - Pushed at: over 2 years ago - Stars: 12 - Forks: 2
Duntrain/dagrad
dagrad is a Python package that provides an extensible, modular platform for developing and experimenting with differentiable (gradient-based) structure learning methods.
Language: Python - Size: 2.91 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 9 - Forks: 1
sfu-cl-lab/FactorBase
The source code repository for the FactorBase system
Language: Java - Size: 208 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 9 - Forks: 6
ogencoglu/causal_twitter_modeling_covid19
Source code for the paper "Causal Modeling of Twitter Activity during COVID-19". Computation, 2020.
Language: Jupyter Notebook - Size: 625 KB - Last synced at: about 1 year ago - Pushed at: almost 2 years ago - Stars: 9 - Forks: 2
QueensGambit/PGM-Causal-Reasoning
Experiments on structure learning of Bayesian Networks with emphasis on finding causal relationship
Language: Jupyter Notebook - Size: 5.64 MB - Last synced at: about 1 year ago - Pushed at: about 6 years ago - Stars: 9 - Forks: 2
syanga/dglearn
Python implementation of "Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs," in ICML 2020
Language: Python - Size: 2.4 MB - Last synced at: about 1 year ago - Pushed at: almost 3 years ago - Stars: 8 - Forks: 0
furrer-lab/abn
Bayesian network analysis in R
Language: R - Size: 82.5 MB - Last synced at: 9 days ago - Pushed at: about 1 month ago - Stars: 6 - Forks: 0
syanga/model-augmented-mutual-information
Code accompanying paper "Model-Augmented Conditional Mutual Information Estimation for Feature Selection" in UAI 2020
Language: Jupyter Notebook - Size: 1.13 MB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 6 - Forks: 0
sergioluengosanchez/TSEM
Tractable learning of Bayesian networks from partially observed data
Language: Python - Size: 131 KB - Last synced at: over 1 year ago - Pushed at: about 6 years ago - Stars: 6 - Forks: 0
Duntrain/TOPO
Optimizing NOTEARS Objectives via Topological Swaps
Language: Python - Size: 57.6 KB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 5 - Forks: 3
fritzbayer/Causal-Discovery-Research-Papers
A curated list of causal structure learning research papers with implementations.
Size: 21.5 KB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 5 - Forks: 0
massimo-rizzoli/BNSL-QA-python
Python implementation of Bayesian Network Structure Learning using Quantum Annealing https://doi.org/10.1140/epjst/e2015-02349-9
Language: Python - Size: 1.96 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 5 - Forks: 1
montilab/shine
Structure Learning for Hierarchical Networks
Language: R - Size: 8.07 MB - Last synced at: 9 days ago - Pushed at: almost 4 years ago - Stars: 5 - Forks: 2
HeddaCohenIndelman/PerturbedStructuredPredictorsDirect
This is the official implementation of the bipartite matching experiment from the paper "Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization".
Language: Python - Size: 58.6 KB - Last synced at: about 2 years ago - Pushed at: almost 4 years ago - Stars: 4 - Forks: 1
tmadeira/tcc
CS undergraduate thesis on uniform generation of k-trees for learning the structure of Bayesian networks (IME-USP 2016).
Language: Go - Size: 7.61 MB - Last synced at: about 2 years ago - Pushed at: almost 7 years ago - Stars: 4 - Forks: 1
python-qds/qdscreen
Quasi-determinism screening for fast Bayesian Network Structure Learning (from T.Rahier's PhD thesis, 2018)
Language: Python - Size: 2.43 MB - Last synced at: 12 days ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 0
jspieler/QBAF-Learning
Structure Learning of Gradual Bipolar Argumentation Graphs using Genetic Algorithms
Language: Python - Size: 1 MB - Last synced at: 5 months ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 1
ArminKaramzade/distributed-sparse-GGM
GGM structure learning using 1 bit.
Language: Python - Size: 24.8 MB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 2 - Forks: 0
noriakis/scstruc
Evaluation of gene regulatory network based on Bayesian network structure in single-cell transcriptomics
Language: R - Size: 7.26 MB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 1 - Forks: 0
JBris/climate-structure-learning-experiments
Structure learning on climate data
Language: Jupyter Notebook - Size: 2.13 MB - Last synced at: 11 days ago - Pushed at: 11 days ago - Stars: 1 - Forks: 0
VishnuBeji/BayesianNet_QuantumAnnealing
Bayesian Network structure learning with encoding into a Quadratic Unconstrained Binary Optimisation (QUBO) problem.
Language: Python - Size: 316 KB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0
ollimacp/spacial-boxcounting-cpu-gpu
A spacial boxcount algorithm is proposed, which encodes incoming data into scaled down version of itself at diffrent scales discribing spacial resolved complexity and heterogenity.
Language: Jupyter Notebook - Size: 51.2 MB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0
erdogant/bnclassify
bnlearn
Language: Python - Size: 35.2 KB - Last synced at: 19 days ago - Pushed at: about 3 years ago - Stars: 1 - Forks: 1
nbegumc/Applying-Bayesian-Networks-to-Wine-Quality-Prediction
Constructing a Bayesian network to capture the dependencies and independencies among variables as well as to predict wine quality
Language: R - Size: 914 KB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0
britojr/btbn
Bounded Tree-width Bayesian Networks learner
Language: Go - Size: 266 KB - Last synced at: 10 months ago - Pushed at: almost 7 years ago - Stars: 1 - Forks: 0
werkaaa/iscm
Standardizing Structural Causal Models, ICLR 2025
Language: Jupyter Notebook - Size: 281 KB - Last synced at: 28 days ago - Pushed at: 28 days ago - Stars: 0 - Forks: 0
dkesada/natPSOHO 📦
Natural Encoding Particle Swarm Optimization Higher-Order Dynamic Bayesian Network Structure Learning in R
Language: R - Size: 1.03 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0
mark-antal-csizmadia/hmm
Hidden Markov Models (HMMs) for estimating the sequence of hidden states (decoding) via the Viterbi algorithm, and estimating model parameters (learning) via the Baum- Welch algorithm.
Language: Jupyter Notebook - Size: 254 KB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0
nvihrs14/tcherry
This R-package is for learning the structure of the type of graphical models called t-cherry trees from data. The structure is determined either directly from data or by increasing the order of a lower order t-cherry tree.
Language: R - Size: 301 KB - Last synced at: 9 days ago - Pushed at: almost 5 years ago - Stars: 0 - Forks: 4
christinabejjani/ClusteredTSMem
Published at Frontiers in Psychology - Cognition (https://www.frontiersin.org/articles/10.3389/fpsyg.2019.02833/full)
Language: HTML - Size: 6.25 MB - Last synced at: about 1 year ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0
purelyvivid/AIA_st2_kaggle_ml
臺灣人工智慧學校(AIA)南部分校技術班第二期 kaggle競賽內容-森林種類預測(DNN)
Language: Jupyter Notebook - Size: 857 KB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0
britojr/kbn
Learn probabilistic models with hidden variables in a k-tree structure
Language: Go - Size: 4.17 MB - Last synced at: about 2 years ago - Pushed at: almost 7 years ago - Stars: 0 - Forks: 0
britojr/lkbn
Latent K-tree Bayesian Networks learner
Language: Go - Size: 249 KB - Last synced at: about 2 years ago - Pushed at: almost 7 years ago - Stars: 0 - Forks: 0
mallika2608/pgm-project
Structure learning for protein signaling pathways
Language: Python - Size: 741 KB - Last synced at: about 2 years ago - Pushed at: about 8 years ago - Stars: 0 - Forks: 0
