Bayesian linear and Gaussian process regression to predict CO2 concentration as a function of time
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Updated
Feb 14, 2017 - MATLAB
Bayesian linear and Gaussian process regression to predict CO2 concentration as a function of time
Ini adalah repository untuk mendokumentasikan hasil penelitian skripsi S1 saya pada prodi Fisika UI
Reproducible code for our paper, "On Causal Discovery with Convergent Cross Mapping"
Learning-based robust sampled-data control for uncertain systems.
This is a fork of the Evolving Gaussian process (EGP) modelling code, which is an extension of GP modelling to evolving systems. Such implementation facilitates sequential model adaptation to incoming data stream.
Code for calibration as a method of design.
Reproducible code for our paper "A Differential Measure of the Strength of Causation"
Gaussian process regression with derivation observations
soil loading optimization with a GP-based soil distribution prediction model
Project source code and data for ML-enhanced risk analysis framework for combustion instability prediction
Surrogate-Assisted Tuning
Codes des TPs de l'UV de Machine Learning de l'EINA
A non-Gaussian distribution is generated from a Gaussian-distributed white noise
Project source code and data for machine-learning-enhanced risk mitigation strategies.
Gaussian process latent variable models with shared latent spaces (SGPLVM)
Reproducible code for our paper "Explainable Learning with Gaussian Processes"
Adaptive Gaussian Process (GP)-based Model Predictive Control (MPC) for Micro Air Vehicles (MAVs)
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