Papers/SSL (4) 썸네일형 리스트형 [짧은 논문 리뷰] Motivation of ConVIRT Title: Contrastive Learning of Medical Visual Representations from Paired Images and Text Venue: arxiv Authors: Yuhao Zhang et al. Date: 2 Oct 2020 Venue: Machine Learning for Healthcare (MLHC) 2022 ConVIRT는 CLIP의 base architecture로 언급되어 읽어 보았습니다. Text-image pair: Medical image (X-ray, CT) 등에 짝이 되는 textual report가 있다고 가정합니다. Pre-training에 사용한 데이터셋 MIMIC-CXR : chest (흉부) radiograph paired with te.. [논문 리뷰] Dimensionality Reduction by Learning an Invariant Mapping (CVPR 2006) Author: Raia Hadsell et al. Paper Link: http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf Concept The Beginning of Contrastive Loss Notation Pairs of samples $\vec X_1, \vec X_2$ Label $Y$ Similar pairs $Y = 0$ Dissimilar pairs $Y = 1$ Energy (L2 norm, Euclidean distance) $D_W$ Loss $L_S, L_D$ Siamese Network $G_W$ Networks sharing parameter $W$ Using $G_W$ when calculating L2 no.. [코드 리뷰] SimCLR Code Review Created: October 10, 2021 5:20 PM This is the report from the class project for code and review reproduction. We utilize the PyTorch version of SimCLR with the most stars. All source codes and rights belong to sthalles/SimCLR and Google Research. Contents Introduction Run SimCLR Code Code Architecture Major Components (§2.1) SimCLR Algorithm to Code Feature Evaluation (§2.3, §4.2) Q&A Reference .. [리뷰] In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning (ICLR 2021) by Rizve et al. Paper Link: https://arxiv.org/pdf/2101.06329.pdf Code Link : https://github.com/nayeemrizve/ups Contents 1. Introduction 2. Related Works 3. Proposed Method 4. Experiments 5. Discussion 6. Summary Abbreviation & Keyword SSL : Semi-supervied Learning PL : Pseudo-labeling CR : Consistency-regularization UPS : Uncertainty-aware pseudo-label selection framework Introduction Deep Lear.. 이전 1 다음
