bayesflow
A Python library for efficient Bayesian modeling with deep learning
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최종 버전 다운로드 (.zip)- bug_report.md
- feature_request.md
- experimental_tests.yml
- multiversion-docs.yaml
- publish.yaml
- style.yaml
- test-docs.yaml
- tests.yaml
- zizmor.yml
- dependabot.yml
- __init__.py
- autodiff.py
- jit.py
- __init__.py
- autodiff.py
- jit.py
- __init__.py
- autodiff.py
- jit.py
- __init__.py
- __init__.py
- as_set.py
- as_time_series.py
- broadcast.py
- concatenate.py
- constrain.py
- convert_dtype.py
- drop.py
- elementwise_transform.py
- expand_dims.py
- filter_transform.py
- group.py
- keep.py
- log.py
- map_transform.py
- nan_to_num.py
- numpy_transform.py
- one_hot.py
- random_subsample.py
- rename.py
- scale.py
- serializable_custom_transform.py
- shift.py
- split.py
- sqrt.py
- squeeze.py
- standardize.py
- take.py
- to_array.py
- to_dict.py
- transform.py
- ungroup.py
- __init__.py
- adapter.py
- __init__.py
- backend_approximator.py
- jax_approximator.py
- tensorflow_approximator.py
- torch_approximator.py
- __init__.py
- compositional.py
- conditions.py
- samplers.py
- __init__.py
- approximator.py
- compositional_approximator.py
- continuous_approximator.py
- ensemble_approximator.py
- model_comparison_approximator.py
- ratio_approximator.py
- scoring_rule_approximator.py
- __init__.py
- nnpe.py
- __init__.py
- augmentations.py
- ensemble_sharing.py
- __init__.py
- disk_dataset.py
- ensemble_dataset.py
- ensemble_indexed_dataset.py
- ensemble_online_dataset.py
- offline_dataset.py
- online_dataset.py
- __init__.py
- accuracy.py
- accuracy_random_points.py
- brier_score.py
- calibration_error.py
- calibration_log_gamma.py
- classifier_two_sample_test.py
- correlation.py
- expected_calibration_error.py
- model_misspecification.py
- posterior_contraction.py
- posterior_z_score.py
- root_mean_squared_error.py
- __init__.py
- bayes_factor_recovery.py
- calibration_ecdf.py
- calibration_ecdf_from_quantiles.py
- calibration_histogram.py
- coverage.py
- loss.py
- mc_calibration.py
- mc_confusion_matrix.py
- mmd_hypothesis_test.py
- pairs_posterior.py
- pairs_quantity.py
- pairs_samples.py
- pairwise_bayes_factors.py
- plot_quantity.py
- recovery.py
- recovery_from_estimates.py
- z_score_contraction.py
- __init__.py
- __init__.py
- diagonal_normal.py
- diagonal_student_t.py
- distribution.py
- mixture.py
- __init__.py
- autoencoder.py
- variational_autoencoder.py
- __init__.py
- free_form_flow.py
- __init__.py
- crossed_design_irt_approximator.py
- single_level_approximator.py
- three_level_approximator.py
- two_level_approximator.py
- __init__.py
- graphical_approximator.py
- inference_conditions.py
- inference_variables.py
- non_exchangeable_wrapper.py
- tensor_concatenation.py
- __init__.py
- crossed_design_irt_simulator.py
- single_level_simulator.py
- three_level_simulator.py
- two_level_simulator.py
- __init__.py
- graphical_simulator.py
- __init__.py
- expanded_graph.py
- inverted_graph.py
- simulation_graph.py
- utils.py
- __init__.py
- latent_inference_network.py
- __init__.py
- __init__.py
- cholesky_factor.py
- leaky.py
- ordered.py
- ordered_quantiles.py
- positive_definite.py
- __init__.py
- kernels.py
- maximum_mean_discrepancy.py
- root_mean_squared_error.py
- __init__.py
- maximum_mean_discrepancy.py
- root_mean_squard_error.py
- __init__.py
- conditional_dense_block.py
- dense_block.py
- diffusion_transformer_block.py
- transformer_feedforward.py
- __init__.py
- featurewise_linear_modulation.py
- fourier_embedding.py
- recurrent_embedding.py
- time2vec.py
- __init__.py
- simple_norm.py
- __init__.py
- sequential.py
- __init__.py
- standardization.py
- standardize.py
- __init__.py
- __init__.py
- consistency_model.py
- stable_consistency_model.py
- __init__.py
- dual_coupling.py
- single_coupling.py
- __init__.py
- fixed_permutation.py
- orthogonal.py
- random.py
- swap.py
- __init__.py
- _rational_quadratic.py
- affine_transform.py
- spline_transform.py
- transform.py
- __init__.py
- actnorm.py
- coupling_flow.py
- invertible_layer.py
- __init__.py
- cosine_noise_schedule.py
- edm_noise_schedule.py
- noise_schedule.py
- __init__.py
- diffusion_model.py
- dispatch.py
- __init__.py
- flow_matching.py
- __init__.py
- brier_score.py
- categorical_scoring_rule.py
- cross_entropy_score.py
- exponential_score.py
- logistic_score.py
- mean_score.py
- median_score.py
- mixture_score.py
- mv_normal_score.py
- normed_difference_score.py
- parametric_distribution_score.py
- polynomial_score.py
- quantile_score.py
- scoring_rule.py
- __init__.py
- point_network.py
- scoring_rule_network.py
- __init__.py
- inference_network.py
- __init__.py
- mlp.py
- time_mlp.py
- __init__.py
- diffusion_transformer.py
- __init__.py
- attention.py
- downsample.py
- residual.py
- time_dense.py
- transformer.py
- upsample.py
- __init__.py
- dense_fourier.py
- __init__.py
- resuvit.py
- unet.py
- uvit.py
- __init__.py
- __init__.py
- convolutional_network.py
- double_conv.py
- __init__.py
- deep_set.py
- equivariant_layer.py
- invariant_layer.py
- __init__.py
- fusion_network.py
- __init__.py
- skip_recurrent.py
- time_series_network.py
- __init__.py
- induced_set_attention.py
- multihead_attention.py
- pooling_by_multihead_attention.py
- set_attention.py
- __init__.py
- fusion_transformer.py
- set_transformer.py
- time_series_transformer.py
- transformer.py
- __init__.py
- summary_network.py
- __init__.py
- defaults.py
- __init__.py
- __init__.py
- benchmark_simulator.py
- bernoulli_glm.py
- bernoulli_glm_raw.py
- gaussian_linear.py
- gaussian_linear_uniform.py
- gaussian_mixture.py
- inverse_kinematics.py
- lotka_volterra.py
- sir.py
- slcp.py
- slcp_distractors.py
- two_moons.py
- __init__.py
- hierarchical_simulator.py
- lambda_simulator.py
- make_simulator.py
- model_comparison_simulator.py
- sequential_simulator.py
- simulator.py
- __init__.py
- shape.py
- tensor.py
- __init__.py
- _populate_all.py
- __init__.py
- calibration_curve.py
- confusion_matrix.py
- __init__.py
- find_cost.py
- find_distribution.py
- find_inference_network.py
- find_network.py
- find_permutation.py
- find_pooling.py
- find_recurrent_net.py
- find_scoring_rule.py
- find_summary_network.py
- find_transform.py
- __init__.py
- minimal_coverage_probs.py
- pointwise_ecdf_bands.py
- ranks.py
- simultaneous_ecdf_bands.py
- __init__.py
- shape_error.py
- __init__.py
- jacobian.py
- jacobian_trace.py
- jvp.py
- vjp.py
- __init__.py
- log_sinkhorn.py
- optimal_transport.py
- ot_utils.py
- sinkhorn.py
- __init__.py
- callbacks.py
- context_managers.py
- decorators.py
- devices.py
- dict_utils.py
- empty.py
- functional.py
- git.py
- hparam_utils.py
- integrate.py
- io.py
- keras_utils.py
- logging.py
- masks.py
- numpy_utils.py
- plot_utils.py
- rng.py
- serialization.py
- tensor_utils.py
- tree.py
- validators.py
- __init__.py
- basic_workflow.py
- compositional_workflow.py
- ensemble_workflow.py
- model_comparison_workflow.py
- workflow.py
- __init__.py
- mamba.py
- mamba_block.py
- __init__.py
- backend_ratio.py
- jax_continuous.py
- jax_dispatch.py
- jax_ratio.py
- jax_wrapper.py
- __init__.py
- neural_distribution.py
- pytensor_ops.py
- ratio_distribution.py
- __init__.py
- __init__.py
- .nojekyll
- CNAME
- Amortized_Point_Estimation.html
- Covid19_Initial_Posterior_Estimation.html
- Hierarchical_Model_Comparison_MPT.html
- Intro_Amortized_Posterior_Estimation.html
- LCA_Model_Posterior_Estimation.html
- Linear_ODE_system.html
- Model_Comparison_MPT.html
- Model_Misspecification.html
- TwoMoons_Bimodal_Posterior.html
- bernoulli_glm.html
- bernoulli_glm_raw.html
- gaussian_linear.html
- gaussian_linear_uniform.html
- gaussian_mixture.html
- inverse_kinematics.html
- lotka_volterra.html
- sir.html
- slcp.html
- slcp_distractors.html
- two_moons.html
- rectifiers.html
- amortizers.html
- attention.html
- benchmarks.html
- computational_utilities.html
- configuration.html
- coupling_networks.html
- default_settings.html
- diagnostics.html
- exceptions.html
- helper_classes.html
- helper_functions.html
- helper_networks.html
- inference_networks.html
- losses.html
- mcmc.html
- sensitivity.html
- simulation.html
- summary_networks.html
- trainers.html
- wrappers.html
- index.html
- bayesflow.amortizers.html
- bayesflow.attention.html
- bayesflow.benchmarks.bernoulli_glm.html
- bayesflow.benchmarks.bernoulli_glm_raw.html
- bayesflow.benchmarks.gaussian_linear.html
- bayesflow.benchmarks.gaussian_linear_uniform.html
- bayesflow.benchmarks.gaussian_mixture.html
- bayesflow.benchmarks.html
- bayesflow.benchmarks.inverse_kinematics.html
- bayesflow.benchmarks.lotka_volterra.html
- bayesflow.benchmarks.sir.html
- bayesflow.benchmarks.slcp.html
- bayesflow.benchmarks.slcp_distractors.html
- bayesflow.benchmarks.two_moons.html
- bayesflow.computational_utilities.html
- bayesflow.configuration.html
- bayesflow.coupling_networks.html
- bayesflow.default_settings.html
- bayesflow.diagnostics.html
- bayesflow.exceptions.html
- bayesflow.experimental.html
- bayesflow.experimental.rectifiers.html
- bayesflow.helper_classes.html
- bayesflow.helper_functions.html
- bayesflow.helper_networks.html
- bayesflow.html
- bayesflow.inference_networks.html
- bayesflow.losses.html
- bayesflow.mcmc.html
- bayesflow.networks.html
- bayesflow.sensitivity.html
- bayesflow.simulation.html
- bayesflow.summary_networks.html
- bayesflow.trainers.html
- bayesflow.version.html
- bayesflow.wrappers.html
- about.html
- examples.html
- genindex.html
- index.html
- installation.html
- py-modindex.html
- search.html
- bayesflow_hex.ico
- bayesflow_hex.png
- bayesflow_hor.png
- bayesflow_hor_dark.png
- bayesflow_landing_dark.png
- bayesflow_landing_light.png
- bayesflow_overview.png
- bf_landing_dark.png
- bf_landing_light.png
- custom.css
- generative_model.png
- base.rst
- custom-module-template.rst
- bayesflow.rst
- index.md
- introduction.md
- pitfalls.md
- serialization.md
- stages.md
- adapt_autodoc_docstring.py
- override_pst_pagetoc.py
- approximators.ipynb
- data_processing.ipynb
- datasets.ipynb
- diagnostics.ipynb
- index.md
- inference_networks.ipynb
- introduction.md
- saving_loading.ipynb
- simulators.ipynb
- summary_networks.ipynb
- workflows.ipynb
- about.rst
- conf.py
- examples.rst
- index.md
- references.bib
- .nojekyll
- generate-redirects.py
- make.bat
- Makefile
- poly.py
- polyversion_patches.py
- pre-build.py
- README.md
- Hyperparameter_Optimization.ipynb
- Joint_Neurocognitive_Model.ipynb
- Stable_Consistency_Model_Playground.ipynb
- mm_gsn.stan
- adaptive_inference.jpg
- c2st_benchmark_boxplot_best.jpg
- diffusion_model_review.jpeg
- example_simulations.png
- fm_cm_visual.jpg
- kinematics_helper.py
- score_visual.jpg
- Bayesian_Experimental_Design.ipynb
- Compositional_Diffusion.ipynb
- Diffusion_Models.ipynb
- Ensembles.ipynb
- From_ABC_to_BayesFlow.ipynb
- From_BayesFlow_1.1_to_2.0.ipynb
- Likelihood_Estimation.ipynb
- Linear_Regression_Starter.ipynb
- Lotka_Volterra_Point_Estimation.ipynb
- Model_Comparison_Deep_Dive.ipynb
- Multimodal_Data.ipynb
- One_Sample_TTest.ipynb
- Ratio_Estimation.ipynb
- SIR_Posterior_Estimation.ipynb
- Spatial_Data_and_Parameters.ipynb
- Two_Moons_Starter.ipynb
- bayesflow_hex.png
- bayesflow_landing_dark.jpg
- bayesflow_landing_light.jpg
- bf_landing_dark.png
- bf_landing_light.png
- __init__.py
- conftest.py
- test_adapters.py
- __init__.py
- conftest.py
- test_approximator_standardization.py
- __init__.py
- conftest.py
- test_build.py
- test_fit.py
- test_log_prob.py
- test_sample.py
- test_save_and_load.py
- __init__.py
- conftest.py
- test_build.py
- test_estimate.py
- test_fit.py
- test_log_prob.py
- test_sample.py
- __init__.py
- conftest.py
- test_model_comparison_approximator.py
- conftest.py
- test_estimate.py
- test_log_prob.py
- test_sample.py
- __init__.py
- conftest.py
- test_ratio_approximator.py
- __init__.py
- conftest.py
- test_build.py
- test_estimate.py
- test_fit.py
- test_log_prob.py
- test_sample.py
- test_save_and_load.py
- __init__.py
- conftest.py
- test_build.py
- test_compositional_approximator.py
- test_fit.py
- test_sample.py
- test_save_and_load.py
- test_summarize.py
- __init__.py
- conftest.py
- test_nnpe.py
- __init__.py
- conftest.py
- test_grad.py
- test_jacfwd.py
- test_jacrev.py
- test_jit.py
- test_jvp.py
- test_side_effects.py
- test_value_and_grad.py
- test_vjp.py
- __init__.py
- __init__.py
- conftest.py
- test_apply_augmentations.py
- test_datasets.py
- test_ensemble_sharing.py
- __init__.py
- conftest.py
- test_diagnostics_metrics.py
- test_diagnostics_plots.py
- __init__.py
- conftest.py
- test_distributions.py
- __init__.py
- conftest.py
- test_examples.py
- __init__.py
- approximator_utils.py
- conftest.py
- test_graphical_approximator.py
- test_inference_conditions.py
- test_inference_variables.py
- test_non_exchangeable_wrapper.py
- test_tensor_concatenation.py
- __init__.py
- conftest.py
- test_graphical_simulator.py
- __init__.py
- conftest.py
- test_expanded_graph.py
- test_graphs_utils.py
- test_inverted_graph.py
- test_simulation_graph.py
- __init__.py
- conftest.py
- test_links.py
- __init__.py
- conftest.py
- test_metrics.py
- __init__.py
- conftest.py
- test_blocks.py
- __init__.py
- conftest.py
- test_consistency_model.py
- __init__.py
- conftest.py
- test_coupling_flow.py
- test_invertible_layers.py
- test_permutations.py
- __init__.py
- conftest.py
- test_compositional_sampling.py
- test_diffusion_model.py
- __init__.py
- conftest.py
- test_flow_matching.py
- __init__.py
- conftest.py
- test_fusion_network.py
- __init__.py
- conftest.py
- test_point_network.py
- test_scoring_rule_network.py
- __init__.py
- conftest.py
- test_sequential.py
- __init__.py
- conftest.py
- test_mlp.py
- test_transformer.py
- test_unet.py
- test_unet_backbones.py
- __init__.py
- conftest.py
- test_convolutional_network.py
- test_deep_set.py
- test_fusion_transformer.py
- test_set_transformer.py
- test_time_series_network.py
- test_time_series_transformer.py
- __init__.py
- conftest.py
- test_attention.py
- test_embeddings.py
- test_inference_networks.py
- test_sample.py
- test_standardization.py
- __init__.py
- conftest.py
- test_scoring_rules.py
- __init__.py
- conftest.py
- test_simulators.py
- conftest.py
- test_two_moons.py
- __init__.py
- conftest.py
- test_classification.py
- test_dispatch.py
- test_ecdf.py
- test_integrate.py
- test_jacobian.py
- test_optimal_transport.py
- test_serialize_deserialize.py
- __init__.py
- conftest.py
- test_basic_workflow.py
- test_compostional_workflow.py
- test_ensemble_workflow.py
- test_model_comparison_workflow.py
- __init__.py
- approximator_checks.py
- assertions.py
- callbacks.py
- check_combinations.py
- jupyter.py
- networks.py
- normal_simulator.py
- ops.py
- __init__.py
- conftest.py
- .gitignore
- .pre-commit-config.yaml
- CITATION.cff
- CODE_OF_CONDUCT.md
- codecov.yml
- CONTRIBUTING.md
- cuda.yaml
- environment.yaml
- LICENSE
- pyproject.toml
- pytest.ini
- README.md
- tox.ini
# 설치 가이드
1. 코드 내려받기
git clone https://github.com/bayesflow-org/bayesflow
깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.
cd bayesflow
방금 내려받은 프로젝트 폴더 안으로 이동합니다.
2. 공식 설치 스크립트
쉬움 추천사전 준비물
- Python 3 pip 명령어를 쓰려면 Python이 필요합니다.
pip install "bayesflow>=2.0"
PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.
pip install git+https://github.com/bayesflow-org/bayesflow.git@dev
PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.
설치 후 새 터미널을 열고, 프로그램의 버전 확인 명령(예: --version)으로 정상 설치됐는지 확인하세요.
이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.
3. Python
쉬움사전 준비물
pip install "bayesflow>=2.0"
PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.
pip install git+https://github.com/bayesflow-org/bayesflow.git@dev
PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.
에러 메시지 없이 실행되고 터미널에 안내 문구가 출력되면 정상입니다.
이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.
4. Make
보통사전 준비물
- Git GitHub에서 프로젝트 코드를 내려받으려면 필요합니다.
- Make Linux/macOS는 보통 기본 설치되어 있습니다. Windows는 별도 설치(예: MSYS2, WSL)가 필요합니다.
cd docsrc
이 프로젝트의 관련 파일이 하위 폴더 안에 있어서, 먼저 그 폴더로 이동합니다.
make
생성된 빌드 설정을 바탕으로 실제 컴파일을 진행해 실행 파일을 만듭니다.
에러 없이 끝나면 성공입니다. 생성된 실행 파일을 직접 실행해보세요.
// repository documentation
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