Open-source framework for uncertainty and deep learning models in PyTorch 🌱

CAIRI Supervised, Semi- and Self-Supervised Visual Representation Learning Toolbox and Benchmark

Simplified PyTorch implementation of image classification, support CIFAR10, CIFAR100, MNIST, custom dataset, multi-gpu training and validating, automatic mixed precision training, knowledge distillation, hyperparameter optimization using Optuna etc.

[Survey] Awesome List of Mixup Augmentation and Beyond (https://arxiv.org/abs/2409.05202)

This repo implements a ViT based model with Mixup Data Augmentation method. All the models including ViT are implemented from scratch using tensorflow

[TMI'20] Learn to Threshold: ThresholdNet with Confidence-Guided Manifold Mixup for Polyp Segmentation

[TMLR] On the Equivalence of Graph Convolution and Mixup

[IEEE TMI 2024] Pseudo-Bag Mixup Augmentation for Multiple Instance Learning-Based Whole Slide Image Classification

About Official PyTorch(MMCV) implementation of “SUMix: Mixup with Semantic and Uncertain Information” (ECCV 2024)

Cambridge UK temperature forecast python notebooks

Model Compression using Knowledge Distillation

Official PyTorch implementation of DiffuseMix : Label-Preserving Data Augmentation with Diffusion Models (CVPR'2024)

Official implementation of "Any Region Can Be Perceived Equally and Effectively on Rotation Pretext Task Using Full Rotation and Weighted-Region Mixture"

[IJCAI 2023] Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation

🛠 Toolbox to extend PyTorch functionalities

PyTorch implementation of 'ViT' (Dosovitskiy et al., 2020) and training it on CIFAR-10 and CIFAR-100

Classification using Vision Transformers (ViT) and MixUp Augmentation

[TAI 2023] Contrastive Domain Adaptation for Time-Series via Temporal Mixup

A handy data augmentation toolkit for image classification put in a single efficient TensorFlow/PyTorch op.