Self-Contrastive Learning: Single-viewed Supervised Contrastive Framework using Sub-network (AAAI 2023)
-
Updated
Oct 28, 2023 - Python
Self-Contrastive Learning: Single-viewed Supervised Contrastive Framework using Sub-network (AAAI 2023)
Medical Diagnosis using Contrastive Learning
This repo contains code for uisng semi-supervised contrastive learning to learn phenotypical representations from Cell Painting image data
Detecting melanomas in images of skin lesions using supervised contrastive learning, and image denoising as a pretext task.
Supervised Contrastive Learning (SupContrast) based on MoCo-v2
Code for MICCAI 2023 publication: SCOL: Supervised Contrastive Ordinal Loss for Abdominal Aortic Calcification Scoring on Vertebral Fracture Assessment Scans
Implemented pose aware face recognition network to Improve the performance of face recognition task for the faces at extreme joint pitch and yaw view angles.
In medical applications with limited training data, traditional self-supervised deep learning struggles for accuracy. This study combines self-supervised learning with Variational Quantum Classifiers (VQC) and Principal Component Analysis (PCA) for dimensionality reduction.
TF 2.x implementation of SupCL (Supervised Contrastive Learning, 2020).
The code repository for the paper: Peijie et al., Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering. IEEE TKDE, 2023.
Implements the ideas presented in https://arxiv.org/pdf/2004.11362v1.pdf by Khosla et al.
Parametric Contrastive Learning (ICCV2021) & GPaCo (TPAMI 2023)
Add a description, image, and links to the supervised-contrastive-learning topic page so that developers can more easily learn about it.
To associate your repository with the supervised-contrastive-learning topic, visit your repo's landing page and select "manage topics."