Bayesian
19 items across the graph — tagged with Bayesian.
From the graph · 19
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causa…
Probabilistic reasoning and statistical analysis in TensorFlow
Bayesian inference with probabilistic programming.
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
High-quality implementations of standard and SOTA methods on a variety of tasks.
Lightweight optimization with local, global, population-based and sequential techniques across mixed search spaces
sbi is a Python package for simulation-based inference, designed to meet the needs of both researchers and practitioners. Whether you need fine-grained control…
A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesia…
Gaussian processes in JAX and Equinox.
Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling metho…
A unified interface for optimization algorithms and experiments
Bayesian Deep Learning: A Survey
Bayesian Optimization and Design of Experiments
Julia package for automated Bayesian inference on a factor graph with reactive message passing
Second Order Optimization and Curvature Estimation with K-FAC in JAX.
An evaluation framework for machine learning models simulating high-throughput materials discovery.
Derivative-free parameter calibration and uncertainty quantification for expensive models using ensemble Kalman methods
Pre-trained Gaussian processes for Bayesian optimization
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