Reinforcement Learning (PyTorch) This repo will contain PyTorch implementation of various fundamental RL algorithms. It’s aimed at making it easy to start playing and learning about RL. The problem I came across investigating other DQN projects is that they either: Don’t have any evidence that they’ve actually achieved the published results Don’t have a “smart” replay buffer (i.e. they allocate (1M, 4, 84, 84) ~ 28 GBs! instead of (1M, 84, 84) ~ 7 GB) Lack of visualizations and debugging […]

CFPNet-M This repository contains the implementation of a novel light-weight real-time network (CFPNet-Medicine: CFPNet-M) to segment different types of biomedical images. It is a medical version of CFPNet, and the dataset we used from top to bottom are DRIVE, ISBI-2012, Infrared Breast, CVC-ClinicDB and ISIC 2018. The details of CFPNet-M and CFPNet can be found here respectively. Architecture of CFPNet-M CFP module CFPNet-M Dataset In this project, we test five datasets: [x] Infrared Breast Dataset [x] Endoscopy (CVC-ClinicDB) [x] Electron […]

ResMLP – Pytorch Implementation of ResMLP, an all MLP solution to image classification out of Facebook AI, in Pytorch Install $ pip install res-mlp-pytorch Usage import torch from res_mlp_pytorch import ResMLP model = ResMLP( image_size = 256, patch_size = 16, dim = 512, depth = 12, num_classes = 1000 ) img = torch.randn(1, 3, 256, 256) pred = model(img) # (1, 1000) Citations @misc{touvron2021resmlp, title = {ResMLP: Feedforward networks for image classification with data-efficient training}, author = {Hugo Touvron and […]

Barlow-Twins-TF This repository iimplements Barlow Twins (Barlow Twins: Self-Supervised Learning via Redundancy Reduction) in TensorFlow and demonstrates it on the CIFAR10 dataset. Summary: With a ResNet20 as a trunk and a 3-layer MLP (each layer containing 2048 units) and 100 epochs of pre-training, this training notebook can give 62.61% accuracy on the CIFAR10 test set. The pre-training total takes ~23 minutes on a single Tesla V100. There are minor differences from the original implementation. However, the original loss function and […]