JOSS Papers: Bayesian optimization

All Papers
3539
 Published Papers
3077
 Active Papers
462
published Published 5 months ago

hetGPy: Heteroskedastic Gaussian Process Modeling in Python

Python C++ Jupyter Notebook R
@davidogara
10.21105/joss.07518
published Published about 1 year ago

Kirstine.jl: A Julia Package for Bayesian Optimal Design of Experiments

Julia
@lsandig
10.21105/joss.06424
published Published about 1 year ago

CalibrateEmulateSample.jl: Accelerated Parametric Uncertainty Quantification

Julia
@odunbar
10.21105/joss.06372
published Published over 1 year ago

PyBADS: Fast and robust black-box optimization in Python

Python
@GurjeetSinghSangra
10.21105/joss.05694
published Published almost 2 years ago

BayesO: A Bayesian optimization framework in Python

Python
@jungtaekkim
10.21105/joss.05320
published Published almost 2 years ago

SBArchOpt: Surrogate-Based Architecture Optimization

Python
@jbussemaker
10.21105/joss.05564
published Published about 2 years ago

RxInfer: A Julia package for reactive real-time Bayesian inference

Jupyter Notebook Julia
@bvdmitri
10.21105/joss.05161
published Published over 2 years ago

EnsembleKalmanProcesses.jl: Derivative-free ensemble-based model calibration

Julia
@odunbar
10.21105/joss.04869
published Published over 2 years ago

DataAssimilationBenchmarks.jl: a data assimilation research framework.

Julia Python
@cgrudz
10.21105/joss.04129
published Published over 6 years ago

hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems

Python C++ Jupyter Notebook
@uvilla
10.21105/joss.00940
Displaying papers 1 - 10 of 12 in total

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ISSN 2475-9066