daozihappy

daozihappy's Stars

• zysymu/AdaMatch-pytorch

  A PyTorch implementation of AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation

  Language:Python263

• xingbowei1/Cross-subject-EEG-Emotion-Recognition-Using-Contrastive-Learning

  Language:Python6

• Lin-Xuejuan/ECNN-C

  Code for paper: EEG-based Emotion Recognition via Efficient Convolutional Neural Network and Contrastive Learning

  51

• JiangChang-BRAIN/MSHCL

  The code for Multi-Scale Hyperbolic Contrastive Learning for Cross-Subject EEG Emotion Recognition.

  Language:Python4

• kekehia123/cl_sster

  Contrastive Learning of Shared SpatioTemporal EEG Representations across individuals

  Language:Jupyter Notebook15

• ziyujia/SST-EmotionNet

  SST-EmotionNet: Spatial-Spectral-Temporal based Attention 3D Dense Network for EEG Emotion Recognition

  Language:Python12225

• Meltemi-Q/eeg-emotion-recognition-domain-subject-adaptation

  EEG Emotion Recognition project, experiment on SEED (SEED-IV), DEAP dataset

  3511

• Abhishek-Iyer1/emotion-classifcation-eeg-seed-ensemble

  Using Deep Learning for Emotion Classification on EEG signals (SEED Dataset). CNN, RNN, Hybrid model, and Ensemble

  Language:Jupyter Notebook6311

• yezi0511/SEED-Emotion-Recognition

  在 SEED 数据集上做 EEG 情绪识别

  10114

• CHEN-XDU/GMSS

  This is an implentation of paper GMSS: Graph-Based Multi-Task Self-Supervised Learning for EEG Emotion Recognition

  Language:Python6312

• tczhangzhi/PyTorch-GANSER

  Official implementation of the paper "GANSER: A Self-supervised Data Augmentation Framework for EEG-based Emotion Recognition"

  Language:Jupyter Notebook656

• NickGreen99/Emotion-Recognition-EEG-Transformer

  Code Implementation of paper: Transformers for EEG-Based Emotion Recognition: A Hierarchical Spatial Information Learning Model

  Language:Python251

• yi-ding-cs/EmT

  This is the pytorch implementation of EmT, a graph-transformer for EEG emotion recognition.

  Language:Python191

• snailpt/CTNet

  CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification

  Language:Jupyter Notebook1282

• renhong-zhang/eeg-emotion-recognition-with-vit

  Use Vision Transformer to generate Emotion Recognition using the DEAP dataset and EEG Signals.

  Language:Python566

• xueyunlong12589/DGCNN

  Repetition code of the model for the paper "EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networks" in pytorch

  Language:Python9117

• XuanhaoLiu/MoGE

  BIBM 24, mixture of graph experts for cross-subject EEG emotion recognitions

  Language:Python51

• CodeBreathing/DMMR

  The official code implementation for "DMMR: Cross-Subject Domain Generalization for EEG-Based Emotion Recognition via Denoising Mixed Mutual Reconstruction"

  Language:Python33

• VoiceBeer/MS-MDA

  Code of paper MS-MDA: Multisource Marginal Distribution Adaptation for Cross-subject and Cross-session EEG Emotion Recognition

  Language:Jupyter Notebook8415

• muzixiang/SI-CLEER

  The source code and data for the paper 'A Supervised Information Enhanced Multi-granularity Contrastive Learning Framework for EEG based Emotion Recognition'

  Language:Python142

• kanhaoning/Self-supervised-group-meiosis-contrastive-learning-for-EEG-based-emotion-recognition

  Language:Python299

• JoeBao22/eeg_seed_test

  The repository contains trials that apply model transformer to the emotion recognition (classification) task based on electroencephalography(EEG).

  Language:Python504

• eeyhsong/EEG-Conformer

  EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.

  Language:Python46262

• chyyuu/os_course_info

  OS Lectures 2022 Spring in Dept. CS, Tsinghua Univ.

  2.9k752

• easezyc/deep-transfer-learning

  A collection of implementations of deep domain adaptation algorithms

  Language:Python897205

• TorchSSL/TorchSSL

  A PyTorch-based library for semi-supervised learning (NeurIPS'21)

  Language:Python1.3k187

• Xiewp/PFAN

  Code for CVPR-2019 paper "Progressive Feature Alignment for Unsupervised Domain Adaptation"

  Language:Python315

• Kinpzz/UDASOD-UPL

  Unsupervised Domain Adaptive Salient Object Detection Through Uncertainty-Aware Pseudo-Label Learning, AAAI Conference on Artificial Intelligence (AAAI), 2022

  Language:Python307

• hellowangqian/UDA-norm-VAE

  Pytorch implementation for the paper: Data augmentation with norm-AE and selective pseudo-labelling for unsupervised domain adaptation

  Language:Python133

• altndrr/clup

  Code implementation of our BMVC 2022 paper: Cluster-level pseudo-labelling for source-free cross-domain facial expression recognition

  Language:Python101