Pinned Repositories
algorithm-visualizer
:fireworks:Interactive Online Platform that Visualizes Algorithms from Code
alles
All small projects that need a place to live, live here. Optimization, numerical methods, graph theory, and more.
Central-Loop-Time-Domain-Electromagnetic-Inversion
Several matlab program for central loop Time Domain Electromagnetic (TDEM) sounding data inversion modelling using various algorithm.
Code-practice
Coursera-ML-AndrewNg-Notes
吴恩达老师的机器学习课程个人笔记
CRN-causal
CTS-Net
The supplemental material and samples with respect to the paper "TWO HEADS ARE BETTER THAN ONE: A TWO-STAGE APPROACH FOR MONAURAL NOISE REDUCTION IN THE COMPLEX DOMAIN" are provided (submitted to ICASSP 2021)
CV
✔（已完结）最全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】
EEGdenoiseNet
EEGdenoiseNet, a benchmark dataset, that is suited for training and testing deep learning-based EEG denoising models, as well as for comparing the performance across different models.
MachineLearning
《统计学习方法》相关的机器学习实现代码。Machine Learning.
2537416852XM's Repositories
2537416852XM/MachineLearning
《统计学习方法》相关的机器学习实现代码。Machine Learning.
2537416852XM/algorithm-visualizer
:fireworks:Interactive Online Platform that Visualizes Algorithms from Code
2537416852XM/alles
All small projects that need a place to live, live here. Optimization, numerical methods, graph theory, and more.
2537416852XM/Central-Loop-Time-Domain-Electromagnetic-Inversion
Several matlab program for central loop Time Domain Electromagnetic (TDEM) sounding data inversion modelling using various algorithm.
2537416852XM/Code-practice
2537416852XM/Coursera-ML-AndrewNg-Notes
吴恩达老师的机器学习课程个人笔记
2537416852XM/CRN-causal
2537416852XM/CTS-Net
The supplemental material and samples with respect to the paper "TWO HEADS ARE BETTER THAN ONE: A TWO-STAGE APPROACH FOR MONAURAL NOISE REDUCTION IN THE COMPLEX DOMAIN" are provided (submitted to ICASSP 2021)
2537416852XM/CV
✔（已完结）最全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】
2537416852XM/EEGdenoiseNet
EEGdenoiseNet, a benchmark dataset, that is suited for training and testing deep learning-based EEG denoising models, as well as for comparing the performance across different models.
2537416852XM/EM-inversion-4-buried-ice
Simple two-dimensional geophysical inversion for permafrost and ground ice detection using electromagnetic methods.
2537416852XM/emagpy
MIRROR of http://gitlab.com/hkex/emagpy Python API and GUI to invert frequency domain electromagnetic data
2537416852XM/exercise
exercise for nndl
2537416852XM/GCRN-complex
2537416852XM/gitskills
2537416852XM/learngit
2537416852XM/LHYML2021-Spring
HW
2537416852XM/ERINN
Electrical resistivity imaging based on deep learning
2537416852XM/External-Attention-pytorch
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
2537416852XM/geophysics-xochimilco-viveros
Data set | Geoelectrical and transient electromagnetic surveys at Viveros de Netzahualcóyotl in Xochimilco, Mexico City, Mexico
2537416852XM/kang-2019-3D-aem
Development of 3D time-domain airborne electromagnetic simulation
2537416852XM/MICEMD
Modeling, inversion and classification in electromagnetic detection
2537416852XM/Multi-Module-Neural-Network-for-EEG-Denoising
2537416852XM/simpegEM1D
Frequency and time domain EM forward modeling and inversion program
2537416852XM/Simple
Experimental Global Optimization Algorithm
2537416852XM/Statistical-Learning-Method_Code
手写实现李航《统计学习方法》书中全部算法
2537416852XM/TEM-ELM
This is a transient electromagnetic inversion code
2537416852XM/TEM-NLnet_demo
This project is for the paper, TEM-NLnet: A Deep Denoising Network for Transient Electromagnetic Signal with Noise Learning
2537416852XM/TEMDnet_demo
This project is for the paper "TEMDnet: A Novel Deep Denoising Network for Transient Electromagnetic Signal with Signal-to-Image Transformation"
2537416852XM/WFTEM3D
A 3D finite-difference transient electromagnetic modeling open-source software, with a MATLAB version, a Fortran version and a Python version.