Unofficial implementation of MLP-Mixer: An all-MLP Architecture for Vision

Try MLP-Mixer in NLP tasks.

Build Image Classification Models with PyTorch.

Vision Transformer (ViT) and MLP-Mixer Comparison | CIFAR10 | PyTorch

Retinal Optical Coherence Tomography (OCT) is a non-invasive imaging technique used to capture high-resolution cross-sections of the retina. With over 30 million OCT scans performed annually, efficient analysis is critical for timely diagnosis.

Implementations of state of the art AI models from scratch

HomebrewNLP in Mesh-TensorFlow flavour for distributed TPU training

모델 학습부터 배포까지 end-to-end 방식으로 이어지는, CV 분야 딥러닝 프로젝트입니다.

GraViT: Transfer Learning with Vision Transformers and MLP-Mixer for Strong Gravitational Lens Discovery

Implementation for paper MLP-Mixer

[ICDEW 2023] Prediction with Time-Series Mixer for the S&P500 Index

Tensorflow/Keras implementation of CV mixer models. [WIP]

This implementation from paper MLP Mixer

In this repository, a very informative and comprehensive implementation of MLP-Mixer is provided for educational purposes using PyTorch.

Implementation for paper MLP-Mixer: An all-MLP Architecture for Vision

Adaptive Vision Transformer for efficient image classification, implementing dynamic token sparsification to reduce computational costs while maintaining accuracy.

The implementation of MLP Mixer which has been a new promising solution for vision task

MLP Mixer (Pytorch): Classify flowers with Flowers dataset and Compare models

Implementing MLP-Mixer by PyTorch (in Colab)

[ACPR2023] The official pytorch implementation of "Increasing diversity of omni-directional images generated from single image using cGAN based on MLPMixer"