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Yue Li's Projects

bloodpressure_ppg_ml icon bloodpressure_ppg_ml

Repository from final conclusion work of Computer Engineering. Estimation of Systolic and Diastolic Blood Pressure Using PPG and ECG Signals and Machine Learning Algorithms

brainmagick icon brainmagick

Training and evaluation pipeline for MEG and EEG brain signal encoding and decoding using deep learning. Code for our paper "Decoding speech perception from non-invasive brain recordings" published in Nature Machine Intelligence, 2023.

char-rnn-tensorflow-1 icon char-rnn-tensorflow-1

Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow

chatterbot icon chatterbot

ChatterBot is a machine learning, conversational dialog engine for creating chat bots

chinesener icon chinesener

A neural network model for Chinese named entity recognition

cnn-mi-bci icon cnn-mi-bci

CNN-SAE program for MI-BCI classification. (Based on "Tabar et al-2016-J Neural Eng. A novel deep learning approach for classification of EEG motor imagery signals")

dagan icon dagan

DAGAN: Data Augmentation Generative Adversarial Networks

deep-learning-for-bci icon deep-learning-for-bci

Resources for Book: Deep Learning for EEG-based Brain-Computer Interface: Representations, Algorithms and Applications

deep-rppg icon deep-rppg

Deep learning (neural network) based remote photoplethysmography: how to extract pulse signal from video using deep learning tools

deep_motion_mag icon deep_motion_mag

Tensorflow implementation of Learning-based Video Motion Magnification

eeg-transformer icon eeg-transformer

A ViT based transformer applied on multi-channel time-series EEG data for motor imagery classification

estimatebp icon estimatebp

An implementation of 'Continuous Systolic and Diastolic Blood Pressure Estimation Utilizing Long Short-term Memory Network' (Frank P.-W. et al.) paper

familia icon familia

A Toolkit for Industrial Topic Modeling

graph_nets icon graph_nets

PyTorch Implementation and Explanation of Graph Representation Learning papers involving DeepWalk, GCN, GraphSAGE, ChebNet & GAT.

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