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aedbo

Adaptive experimental design using Bayesian optimization to improve the cost efficiency of small-plot field trials

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

bayesian-experimental-design-coupling-with-multi-fidelity-gaussian-processes

Bayesian Experimental Design Coupling with Multi-fidelity Gaussian Processes (co-kriging) for Estimation of Hydraulic Conductivity in a Watershed

bayesian-parameter-estimation__markov-chain-monte-carlo__type-1-diabetes

Bayesian parameter estimation approach using MCMC technique is designed to identify the model of glucose-insulin dynamics using both experimental and simulation data. Experimental data from a real patient with type 1 diabetes using subcutaneous pump therapy who participated in a clinical research study is used

bayesopt

BayesOpt: A toolbox for bayesian optimization, experimental design and stochastic bandits.

bedimplicit

Source code for "Efficient Bayesian Experimental Design for Implicit Models" - https://arxiv.org/abs/1810.09912

benchmark-models-petab

A collection of mathematical models with experimental data in the PEtab format as benchmark problems in order to evaluate new and existing methodologies for data-based modelling

book-csapp

深入理解计算机系统(Computer Systems: A Programmer's Perspective)

dad

Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design

edbo

Experimental Design via Bayesian Optimization

emukit

A Python-based toolbox of various methods in uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.

experimental-design

A Course on designing high-throughput experiments

lmis-oed

Code for "A layered multiple importance sampling scheme for focused optimal Bayesian experimental design"

pinns

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

pytorch-tutorial

Build your neural network easy and fast

sbinns

visid

Visualization of Identifiability Problems in Dynamic Biochemical Models