XuanhaoLiu

LGG

[TNNLS-2023] This is the PyTorch implementation of LGGNet.

GMSS

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

LaBraM

ICLR 2024 spotlight

AIGC-Brain

Brain-Conditional Multimodal Synthesis: A Survey and Taxonomy

Signal-feature-extraction_DE-and-PSD

Code for extracting DE (differential entropy) and PSD (power spectral density) feature of signals.

stable-diffusion

A latent text-to-image diffusion model

CLIP

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

Tune-A-Video

[ICCV 2023] Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation

MindVideo

Official code base for MinD-Video

Simple_Reinforcement_Learning

spikformer

ICLR 2023, Spikformer: When Spiking Neural Network Meets Transformer

BrainBERT

[ICLR 2023] Code for BrainBERT

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.

mixture-of-experts

PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538

PFLlib

We expose this user-friendly algorithm library (with an integrated evaluation platform) for beginners who intend to start federated learning (FL) study

DenoisingDiffusionProbabilityModel-ddpm-

This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.

Generalizable-Mixture-of-Experts

GMoE could be the next backbone model for many kinds of generalization task.

CrossCultureCode

mixup-cifar10

mixup: Beyond Empirical Risk Minimization

ML-Leaks

Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"

annotated_deep_learning_paper_implementations

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠