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100-days-of-ml-code

100-Days-Of-ML-Code中文版

a-polynomial-regression-machine-learning-approach-for-reliability-based-optimization

This is a compact code for reliability analysis under uncertainty using a Polynomial Regression Machine Learning approach. The code implements a stochastic response surface method (SRSM) which quantifies the uncertainty in a performance function for the purpose of reliability-based design optimization (RBDO).

active-subspace_paul-g.-constantine

amk-mcs-aeff

an active-learning method for reliability analysis based on multi-fidelity kriging model

apce

Matlab codes for Arbitrary Polynomial Chaos Expansion

applied-deep-learning

Applied Deep Learning Course

autosdaplatform

awesome-meta-learning

A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.

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

bayesoptbook.github.io

Companion webpage for the book "Bayesian Optimization" by Roman Garnett

bcs

Bayesian Compressive Sensing and Multi-task Compressive Sensing

bp-rbf-prediction

使用BP神经网络、RBF神经网络以及PSO优化的RBF神经网络进行数据的预测

cessipy

collapse_consistent_protocols

This Matlab code implements the developed collapse-consistent protocols for experimental testing of steel columns under cyclic loading

complete-python-3-bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

damage-resistant-structure

data_driven_science_python_demos

IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by J. Nathan Kutz and Steven L. Brunton

deep_euler_tests

Codes for testing the Deep Euler Method

deepcnns-surrogate-uq

Deep convolutional neural networks for random field uncertainty propagation

deeplstm

Deep LSTM for highly nonlinear system modeling

ditto

Eclipse Ditto™ Project

dreaminsg-integrated-model

An integrated water-power-transportation model for network simulations.

emukit

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

eqdiscovery

Physics-informed learning of governing equations from scarce data

erd2

Earthquake Responses prediction using Deep learning and Database

esl-cn

The Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。

fm-2d

Open-source MATLAB-based computational platform for modeling and analyzing steel frame buildings in OpenSEES.

gf-discrepancy-based-point-selection

gnn-lstm-based-fusion-model-for-structural-dynamic-responses-prediction

A novel GNN-LSTM-based fusion model which could accurately predict the seismic responses of multiple structures with different geometry.

gpax

Structured Gaussian Processes and Deep Kernel Learning