Graph Neural Network Library for PyTorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

Python package built to ease deep learning on graph, on top of existing DL frameworks.

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

An Autonomous LLM Agent for Complex Task Solving

Implementation of Graph Convolutional Networks in TensorFlow

A Collection of Variational Autoencoders (VAE) in PyTorch.

A list of popular github projects related to deep learning

Graph Convolutional Networks in PyTorch

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

A Keras implementation of CapsNet in NIPS2017 paper "Dynamic Routing Between Capsules". Now test error ＝ 0.34%.

NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing

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

Implement Statistical Learning Methods, Li Hang the hard way. 李航《统计学习方法》一书的硬核 Python 实现

A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.

Deep learning software to decode EEG, ECG or MEG signals

Keras-based implementation of Relational Graph Convolutional Networks

Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python

InceptionTime: Finding AlexNet for Time Series Classification

Python script to stream EEG data from the muse 2016 headset

Flexible components pairing 🤗 Transformers with ⚡ Pytorch Lightning

Hyperbolic Graph Convolutional Networks in PyTorch.

本科毕设内容：基于卷积神经网络的疲劳驾驶检测。

Biosignal Processing in Python

Wasserstein Auto-Encoders

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

EEG Experiments in Python

Implementation of R-GCNs for Relational Link Prediction