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3dinversion

adcme.jl

Automatic Differentiation Library for Computational and Mathematical Engineering

awesome-public-datasets

A topic-centric list of HQ open datasets.

clinical-history

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被55个国家的300所大学用于教学。

dagantzj

DAGANTZJ for GTA5

deeplabv3

the implement of deeplabv3 for the next work

easy-rl

强化学习中文教程（蘑菇书），在线阅读地址：https://datawhalechina.github.io/easy-rl/

executables

MODFLOW and related program executables for Windows, Mac, and Linux

eyetracking-to-find-the-areaofinterest

This project is about trasking the user eye movement and finding the particular Area of Interest from the whole screen. Its application starts from using it give more personalised advertisements based on which region our eye is looking upon, It can be used to detect our concentration level by monitoring our eye movement etc

fcn16s

the tensorflow implement of FCN16S in FCN

fdmodelbuildingcoursegroundwaterflow

Finite difference model building and application course in Python (jupyter notebooks)

finetune_alexnet_for_hash

the practice of Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks

flopy

A Python package to create, run, and post-process MODFLOW-based models.

gazeclustering

A data-analysis pipeline for Clustering of Gaze Location (detecting areas of interest) and testing different clustering methods

gpytorch

A highly efficient implementation of Gaussian Processes in PyTorch

hamiltonian-nn

Code for our paper "Hamiltonian Neural Networks"

knifegate_pan

deeplabv3 for knife dataset

kpca

Kernel PCA and Pre-Image Reconstruction

machine-learning-models

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

machine_learning_homework

machine_learning_homework

multiclasssvm

Experiments on creating an SVM that can perform multi-class classification

neural-pde-solver

patternrecognition_matlab

Feature reduction projections and classifier models are learned by training dataset and applied to classify testing dataset. A few approaches of feature reduction have been compared in this paper: principle component analysis (PCA), linear discriminant analysis (LDA) and their kernel methods (KPCA,KLDA). Correspondingly, a few approaches of classification algorithm are implemented: Support Vector Machine (SVM), Gaussian Quadratic Maximum Likelihood and K-nearest neighbors (KNN) and Gaussian Mixture Model(GMM).

percnn

Encoding physics to learn reaction-diffusion processes

pga_lstm

Physics Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modelling

pinns

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

project-based-learning

Curated list of project-based tutorials

pykan

Kolmogorov Arnold Networks

resnet50fcn

the compare experiment