Xiong Daowen's repositories
AISystem
AISystem 主要是指AI系统，包括AI芯片、AI编译器、AI推理和训练框架等AI全栈底层技术
brain-inspired-replay
A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).
BraVL_fork
Code and Data for "Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features"
CVAE-GAN-zoos-PyTorch-Beginner
For beginner, this will be the best start for VAEs, GANs, and CVAE-GAN. This contains AE, DAE, VAE, GAN, CGAN, DCGAN, WGAN, WGAN-GP, VAE-GAN, CVAE-GAN. All use PyTorch.
EEG-Conformer
EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.
eeg_encoding
Using DNNs to build encoding models of EEG visual responses.
EEG_Image_decode
Using vision-language models to decode natural image perception from non-invasive brain recordings.
EEGRAPH
EEGraph: Convert EEGs to graphs with frequency and time-frequency domain connectivity measures.
Emotion_Neurophysio_IS-RSA
Scripts for the emotion EEG, ECG, sociability ISRSA analysis
generative-models
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
imagery-master
Notebooks and code relating to "Generative feedback explains distinct brain activity codes for seen and mental images"
Integrated-Design-Diffusion-Model
IDDM (Industrial, landscape, animate...), support DDPM, DDIM, PLMS, webui and multi-GPU distributed training. Pytorch实现，生成模型，扩散模型，分布式训练
latex_paper_writing_tips
Tips for Writing a Research Paper using LaTeX
ml-visuals
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
mmvae
Multimodal Mixture-of-Experts VAE
NICE-EEG
[ICLR 2024] EEG-based image decoding. i. Propose a contrastive learning framework to align image and eeg. ii. Resolving brain activity for biological plausibility.
pytorch-practice
Some example scripts on pytorch
RGCNN-pyg
Examples of the use of PYG
VAE-CVAE-MNIST
Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch