Renhao Ye (Rh-YE)

Rh-YE

Geek Repo

Company:Shanghai Astronomical Observatory

Location:Shanghai,China

Home Page:www.astre2galaxy.com

Github PK Tool:Github PK Tool

Renhao Ye's starred repositories

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GALMoss

a galaxy surface bightness fitting code via gradient descent

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aisys-building-blocks

Building blocks for foundation models.

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FocusOnSlang-Toolbox

Official repository of paper "SLANG: New Concept Comprehension of Large Language Models"

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NSFC-application-template-latex

国家自然科学基金申请书正文(面上项目)LaTeX 模板(非官方)

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GraXpert

GraXpert is an astronomical image processing program for extracting and removing gradients from the background of your astrophotos.

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freegecko

Config files for my GitHub profile.

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academicpages.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

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legacypipe

Image reduction pipeline for the DESI Legacy Imaging Surveys, using the Tractor framework

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ffhq-dataset

Flickr-Faces-HQ Dataset (FFHQ)

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stylegan-t

[ICML'23] StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis

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stylegan-xl

[SIGGRAPH'22] StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets

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SCALE

[ICLR 2024] Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement.

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pfgmpp

Code for ICML 2023 paper, "PFGM++: Unlocking the Potential of Physics-Inspired Generative Models"

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imagine

The code that runs http://legacysurvey.org/viewer -- map-like viewer for astronomical images, especially the Dark Energy Camera Legacy Survey

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ash

Code release for paper Extremely Simple Activation Shaping for Out-of-Distribution Detection

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StarWhisper

StarWhisper:LLM for Astronomy

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SHE_ood_detection

OOD detection based on Hopfield Energy (published on ICLR2023)

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Poisson_flow

Code for NeurIPS 2022 Paper, "Poisson Flow Generative Models" (PFGM)

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galight

A python package that decompose the light into PSF and Sersic, fitting based on lenstronomy

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CleanMyWechat

自动删除 PC 端微信缓存数据,包括从所有聊天中自动下载的大量文件、视频、图片等数据内容,解放你的空间。

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zihao_course

同济子豪兄的公开课

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SHOT

code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"

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UTR

Code for paper "Source Data and Target Annotations Agnostic Transferability Representation for Source-Free Unsupervised Domain Adaptation"

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Awesome-Novel-Class-Discovery

A list of papers that studies Novel Class Discovery

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awesome_OpenSetRecognition_list

A curated list of papers & resources linked to open set recognition, out-of-distribution, open set domain adaptation and open world recognition

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