Fast and robust Bayesian inference using Gaussian processes with GPry
J El Gammal, N Schöneberg, J Torrado… - Journal of Cosmology …, 2023 - iopscience.iop.org
We present the GPry algorithm for fast Bayesian inference of general (non-Gaussian)
posteriors with a moderate number of parameters. GPry does not need any pre-training …
posteriors with a moderate number of parameters. GPry does not need any pre-training …
PyBADS: Fast and robust black-box optimization in Python
PyBADS is a Python implementation of the Bayesian Adaptive Direct Search (BADS)
algorithm for fast and robust black-box optimization (Acerbi and Ma 2017). BADS is an …
algorithm for fast and robust black-box optimization (Acerbi and Ma 2017). BADS is an …
BlackBIRDS: Black-Box Inference foR Differentiable Simulators
BlackBIRDS is a Python package consisting of generically applicable, black-box inference
methods for differentiable simulation models. It facilitates both (a) the differentiable …
methods for differentiable simulation models. It facilitates both (a) the differentiable …
BCI Toolbox: An open-source python package for the Bayesian causal inference model
Psychological and neuroscientific research over the past two decades has shown that the
Bayesian causal inference (BCI) is a potential unifying theory that can account for a wide …
Bayesian causal inference (BCI) is a potential unifying theory that can account for a wide …
[PDF][PDF] CalibrateEmulateSample. jl: Accelerated Parametric Uncertainty Quantification
R Oliver, M Bieli, A Garbuno-Iñigo… - Journal of Open …, 2024 - joss.theoj.org
A Julia language (Bezanson et al., 2017) package providing practical and modular
implementation of “Calibrate, Emulate, Sample”(Cleary et al., 2021), hereafter CES, an …
implementation of “Calibrate, Emulate, Sample”(Cleary et al., 2021), hereafter CES, an …
LINFA: a Python library for variational inference with normalizing flow and annealing
Variational inference is an increasingly popular method in statistics and machine learning
for approximating probability distributions. We developed LINFA (Library for Inference with …
for approximating probability distributions. We developed LINFA (Library for Inference with …