nmningmei
consciousness,metacognition,semantic processing,fMRI,M/EEG,generative models.
Shenzhen UniversityShenzhen, Guangdong, China
Pinned Repositories
BOLD5000_autoencoder
autoencoder trained on BOLD5000 dataset
Deep_learning_fMRI_EEG
Implementation of deep learning models in decoding fMRI/EEG data in a context of semantic processing
Get_Sleep_data
Get the EEG sleep data from OSF "Nap EEG"
intuitive_probability_games
metasema_encoding_based_RSA
METASEMA_encoding_model
Decoding and encoding models reveal the role of mental simulation in the brain representation of meaning
parametric_nonparametric_statistics_comparison
A comparion between parametric and nonparametric statistics using Python
plot_atlas
plot fMRI ROIs with different colors
preprocessing_pipelines
Preprocessing Pipelines for EEG (MNE-python), fMRI (nipype), MEG (MNE-python/autoreject) data
unconfeats
nmningmei's Repositories
nmningmei/SpindleClassification_DeepConvolutionalNeuralNets
Feature Engineering for Sleep Spindle classification
nmningmei/MNE-python-BCBL-course
Collections of scripts
nmningmei/psychopy_experiments
psychopy psychophysics experiments
nmningmei/melody_embedding
embedding audio
nmningmei/AlphaAI
Use unsupervised and supervised learning to predict stocks
nmningmei/Architecture-DCGAN
DCGAN in Pytorch trained on a custom architecture dataset.
nmningmei/arl-eegmodels
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
nmningmei/brainiak
Brain Imaging Analysis Kit
nmningmei/Costs-in-living-these-cities
Stacked bar graph of costs in living in 50 popular cities, data from Chief.
nmningmei/d2l-pytorch
This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.
nmningmei/dichotic-listening-of-tones-is-influenced-by-the-content-of-speech
nmningmei/dsae-torch
Deep Spatial Autoencoders in PyTorch
nmningmei/Fast-Texforms
Code database for Fast Texform generation as proposed in the work of Deza, Chen, Long and Konkle (CCN 2019).
nmningmei/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
nmningmei/in-60-seconds
GitPitch In 60 Seconds - A Very Short Tutorial
nmningmei/Julia-on-Colab
Notebook for running Julia on Google Colab
nmningmei/jupyter
Jupyter metapackage for installation, docs and chat
nmningmei/kobe_shot
simply because someone collected all of Kobe's shots
nmningmei/Machine-Learning-Decal-Spring-2019
A 2-unit decal run by ML@B's education team
nmningmei/MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
nmningmei/modification-pipelines
nmningmei/multitask
Code for Task representations in neural networks trained to perform many cognitive tasks
nmningmei/OMG_collaborate_project
OMG emotional challenge
nmningmei/openpose_capture
use posepose to capture temporal information
nmningmei/ppl-api
A comparison of PPL APIs
nmningmei/practicalAI
A practical approach to learning machine learning.
nmningmei/project_CBA
a simple analysis of Chinese Basketball Association in the past 3 years
nmningmei/pytorch_model_summary
nmningmei/simulation
nmningmei/Text_Classification
Text Classification Algorithms: A Survey