Erjian96

LLMs_interview_notes

LLMs interview notes and answers:该仓库主要记录大模型（LLMs）算法工程师相关的面试题和参考答案

Awesome-Medical-LLM

Large language model of Medical AI, General Medical AI (GMAI)

LRA-diffusion

This is the source code of LRA-diffusion for learning from noisy labels

Label-Free-Scene-Understanding

Med-MMHL

Med-MMHL dataset

DocTamper

[CVPR2023] Towards Robust Tampered Text Detection in Document Image: New Dataset and New Solution

LViT

[IEEE Transactions on Medical Imaging/TMI] This repo is the official implementation of "LViT: Language meets Vision Transformer in Medical Image Segmentation"

SimiFeat

leetcode-master

《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀

comp

[NeurIPS 2017] [ICML 2019] Code for complementary-label learning

NLNL-Negative-Learning-for-Noisy-Labels

NLNL: Negative Learning for Noisy Labels

2022-TPAMI-SURE

PyTorch implementation for Robust Multi-view Clustering with Incomplete Information (TPAMI 2022).

RINCE

CVPR 2022, Robust Contrastive Learning against Noisy Views

reco

The implementation of "Bootstrapping Semantic Segmentation with Regional Contrast" [ICLR 2022].

cma

Contrastive Model Adaptation for Cross-Condition Robustness in Semantic Segmentation [ICCV 2023]

SPML

Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning

awesome-data-augmentation

This is a list of awesome methods about data augmentation.

AutoGPT

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

react-demos

a collection of simple demos of React.js

Sam_LoRA

Low rank adaptation for segmentation anything model (SAM)

wseg

[CVPR'22] Weakly Supervised Semantic Segmentation by Pixel-to-Prototype Contrast

ChatDoctor

CIR

SpatialCorrection

Learning to Segment from Noisy Annotations: A Spatial Correction Approach

Co-teaching

NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels

nnUNet

Advances-in-Label-Noise-Learning

A curated (most recent) list of resources for Learning with Noisy Labels

Provably-end-to-end-label-noise-learning-without-anchor-points

STswinCL

[TMI'22]Exploring Intra- and Inter-Video Relation for Surgical Semantic Scene Segmentation

EndoVis2018

MICCAI challenge for EndoVis2018