Pinned Repositories
academicpages.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Active-Expansion-Sampling
Experiment code associated with our paper: "Active Expansion Sampling for Learning Feasible Domains in an Unbounded Input Space"
AdaptiveMIVor
MIVor: An innovative adaptive Kriging approach for efficient problem classification.
Decision-Making-Under-Uncertainty
Decision making under uncertainty using the POMDPs.jl ecosystem taught by Robert Moss
deep-uq-paper
A repository that contains scripts to replicate results in the Deep UQ paper.
Efficient_Global_Optimization_Algorithms
standard, parallel, constrained, and multiobjective EGO algorithms
PCE_NARX
RALAB
The source codes of RALAB
tongcezhou's Repositories
tongcezhou/Decision-Making-Under-Uncertainty
Decision making under uncertainty using the POMDPs.jl ecosystem taught by Robert Moss
tongcezhou/Efficient_Global_Optimization_Algorithms
standard, parallel, constrained, and multiobjective EGO algorithms
tongcezhou/PCE_NARX
tongcezhou/academicpages.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
tongcezhou/RALAB
The source codes of RALAB
tongcezhou/An-expected-uncertainty-reduction-of-reliability-adaptive-sampling-convergence-criterion-for-Krigin
tongcezhou/batchbald_redux
Reusable BatchBALD implementation
tongcezhou/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
tongcezhou/Beamer-LaTeX-Themes
Customized beamer templates based on SINTEF Presentation template
tongcezhou/bernoulli_lse
Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation
tongcezhou/BSC_RLCB
The code is used to solve structural reliability analysis problem via the BSC_RLCB method
tongcezhou/dcekit
DCEKit (Data Chemical Engineering toolKit)
tongcezhou/DeepONet-reliability
tongcezhou/digital-twin-SHM
tongcezhou/EasySurrogate
The VECMA toolkit for creating surrogate models of multiscale systems.
tongcezhou/emukit
A Python-based toolbox of various methods in uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.
tongcezhou/Max-value-Entropy-Search
Max-value Entropy Search for Efficient Bayesian Optimization
tongcezhou/MF-BSC-Believer
This code is used to evaluation the component reliability analysis through MF-BSC-Believer algorithm
tongcezhou/mf2
Collection of Multi-Fidelity benchmark functions
tongcezhou/modAL
A modular active learning framework for Python
tongcezhou/OpenCossan
OpenCossan is an open and free toolbox for uncertainty quantification and management.
tongcezhou/OpenSeesPy-Examples
This is a more pythonic implementation of OpenSeesPy library to model and analyze structural problems in Jupyter notebooks
tongcezhou/openturns
Uncertainty treatment library
tongcezhou/pyapprox
tongcezhou/pyrelational
pyrelational is a python active learning library for rapidly implementing active learning pipelines from data management, model development (and Bayesian approximation), to creating novel active learning strategies.
tongcezhou/RBDO-Matlab-Double-Loop
This Matlab files are used to demonstrate on how to perform Reliability-based Design Optimization (RBDO) using FERUM. Two approaches are used namely: Reliability Index Approach (RIA) and Performance Measure Approach.
tongcezhou/review-response-template
LaTeX template for the response to reviewer comments (scientific journal publications)
tongcezhou/smt
Surrogate Modeling Toolbox
tongcezhou/stk
The STK is a (not so) Small Toolbox for Kriging. Its primary focus is on the interpolation/regression technique known as kriging, which is very closely related to Splines and Radial Basis Functions, and can be interpreted as a non-parametric Bayesian method using a Gaussian Process (GP) prior.
tongcezhou/uncertainty-toolbox
A python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization