Pinned Repositories
AdapGL-pytorch
ASTGCN-r-pytorch
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting, AAAI 2019, pytorch version
ASTTN_pytorch
BraVL
Code and Data for "Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features"
DataStructure-BeautyOfAlgorithm
《数据结构与算法之美》的学习笔记和python代码实现
deep-learning-time-series
List of papers, code and experiments using deep learning for time series forecasting
DGCN
The code of paper "A Novel Representation Learning for Dynamic Graphs Based on Graph Convolutional Networks, IEEE Transactions on Cybernetics".
DGCNN
Repetition code of the model for the paper "EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networks" in pytorch
dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
DS-DDPM
Implementation of Domain Specific Denoising Diffusion Probabilistic Models for Brain Dynamics/EEG Signals
jukebox333's Repositories
jukebox333/ASTTN_pytorch
jukebox333/BraVL
Code and Data for "Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features"
jukebox333/DataStructure-BeautyOfAlgorithm
《数据结构与算法之美》的学习笔记和python代码实现
jukebox333/deep-learning-time-series
List of papers, code and experiments using deep learning for time series forecasting
jukebox333/DGCN
The code of paper "A Novel Representation Learning for Dynamic Graphs Based on Graph Convolutional Networks, IEEE Transactions on Cybernetics".
jukebox333/DGCNN
Repetition code of the model for the paper "EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networks" in pytorch
jukebox333/dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
jukebox333/DS-DDPM
Implementation of Domain Specific Denoising Diffusion Probabilistic Models for Brain Dynamics/EEG Signals
jukebox333/dynamic_brain_graph_structure_learning
Minimal PyTorch implementation of Dynamic Brain Graph Structure Learning (Campbell 2022)
jukebox333/eeg-gcnn
Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (with an oral spotlight!) at ML4H Workshop, NeurIPS 2020.
jukebox333/STGCN
The PyTorch version of STGCN.
jukebox333/EEG-DL
A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.
jukebox333/eeg-gnn-ssl
jukebox333/eeg_encoding
Using DNNs to build encoding models of EEG visual responses.
jukebox333/gnn4lp
gnn for link prediction，图神经网络用于链接预测。
jukebox333/Graph-Learning
Graph model implementation
jukebox333/graphs4mer
jukebox333/LGG
[TNNLS-2023] This is the PyTorch implementation of LGGNet.
jukebox333/lihang-code
《统计学习方法》的代码实现
jukebox333/machine-learning-course
浙江大学胡浩基《机器学习》代码
jukebox333/MegaCRN
[AAAI23] This it the official github for AAAI23 paper "Spatio-Temporal Meta-Graph Learning for Traffic Forecasting"
jukebox333/MVS-GCN
The official implementation of MVS-GCN
jukebox333/paper-reading
深度学习经典、新论文逐段精读
jukebox333/pytorch-GAT
My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!
jukebox333/RGSL
jukebox333/Shu_Dataset
Scripts de procesamiento y experimentos de la base de datos.
jukebox333/stagin
STAGIN: Spatio-Temporal Attention Graph Isomorphism Network
jukebox333/T-GCN
Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method
jukebox333/Time-Series-Library
A Library for Advanced Deep Time Series Models.
jukebox333/zihao_course
同济子豪兄的公开课