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"
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Jan 14, 2024 - Python
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structure-learning
Here are 37 public repositories matching this topic...
Repository of a data modeling and analysis tool based on Bayesian networks
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Nov 10, 2025 - Python
[Experimental] Global causal discovery algorithms
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Oct 19, 2026 - Python
Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
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Mar 31, 2024 - Python
Scalable open-source software to run, develop, and benchmark causal discovery algorithms
benchmarking reproducible-research graphical-models causality bayesian-networks structure-learning causal-models markov-networks snakemake-workflow causal-discovery
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Oct 9, 2026 - Python
Amortized Inference for Causal Structure Learning, NeurIPS 2022
transformers causality variational-inference causal-inference structure-learning amortized-inference causal-discovery
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Feb 11, 2025 - Python
Graph Optimiser for Learning and Evolution of Models
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Sep 30, 2026 - Python
DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021
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Feb 27, 2024 - Python
Document Image Classification with Intra-Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks
deep-learning image-classification document-classification transfer-learning structure-learning deep-convolutional-neural-networks document-image-classification training-strategies
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Nov 16, 2019 - Python
Sum-Product Network learning routines in python
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Jun 10, 2015 - Python
dagrad is a Python package that provides an extensible, modular platform for developing and experimenting with differentiable (gradient-based) structure learning methods.
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May 8, 2025 - Python
Lightweight PC algorithm for causal skeleton discovery — pip + CLI + graph viz
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Jul 31, 2026 - Python
Bayesian network structure learning
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May 22, 2022 - Python
[SDM'23] ML4C: Seeing Causality Through Latent Vicinity
graph supervised-learning discrete causality structure-learning causal causality-algorithms causal-discovery supervised-causal-learning
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Nov 9, 2022 - Python
Optimizing NOTEARS Objectives via Topological Swaps
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Sep 30, 2024 - Python
Python implementation of Bayesian Network Structure Learning using Quantum Annealing https://doi.org/10.1140/epjst/e2015-02349-9
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Sep 28, 2022 - Python
Chow-Liu algorithm learning optimal tree-structured Bayesian Networks from mutual information matrices via maximum weight spanning trees.
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Sep 9, 2026 - Python
Chow-Liu algorithm learning optimal tree-structured Bayesian Networks from mutual information matrices via maximum weight spanning trees.
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Sep 9, 2026 - Python
Tractable learning of Bayesian networks from partially observed data
bayesian-network structure-learning incomplete-data structural-expectation-maximization inference-complexity
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Feb 25, 2019 - Python
Python implementation of "Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs," in ICML 2020
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Jun 2, 2022 - Python
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