Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond - NeurIPS 2023

Contrastive Unlearning

This project has a comprehensive exploration of two key topics: Softmax Regression and Contrastive Representation Learning. The dataset used for this project is the CIFAR-10 dataset, which can be accessed by link given below

Neural inverted index for fast and effective information retrieval

'24su deep daiv Medical AI 음파음파 팀 (24/08/01 ~ 24/10/05) | 코로나 음성데이터와 환자 메타 데이터를 활용한 대조학습 (In Progress)

Contrastive Language-Image Pretraining

Occluded facial expression recognition using contrastive learning to improve performance on occluded images while retaining performance on non-occluded ones.

Solution to the NeurIPS 2022 competition: Cross Domain MetaDL

Supervised Contrastive Learning for Diabetic Retinopathy Classification

Contrastive Learning in JAX

Geometric-aware Graph Attention Networks

Implementation of a Simple Siamese network for contrastive learning in tensorflow2.0

CoLMoC - Contrastive Learning based Molecular Clustering

In this project, we aim to classify product categories (based on the Google taxonomy) and brands using fine-tuned CLIP embeddings. Our primary focus will be on aggregating textual and image embeddings to achieve a more representative depiction of the products, leading to enhanced performance.

A contrastive learning approach for integration of high-content screens

Contrastive Learning of Medical Visual Representations from Paired Images and Text

📎 Korean CLIP

Contrastive representation learning with PyTorch

This repository stores work for a seminar for my master's degree. The course is held from the chair Intelligent Embedded Systems (IES). My topic is Approaches for finding sample pairs in contrastive learning.