Skip to content
View WolffeM's full-sized avatar
💭
I may be slow to respond.
💭
I may be slow to respond.
8 followers · 292 following

Block or report WolffeM

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
WolffeM/README.md
  • 👋 Hi, I’m @WolffeM
  • 👀 I’m interested in theoretical cosmology and numerical simulations
  • 🌱 I’m currently learning N-body simulation, ML methods
  • 💞️ I’m looking to collaborate on cosmological simulation for CMB, foregrounds, Quasar/Galaxies Surveys, 21cm.
  • 📫 How to reach me: [email protected]

Popular repositories Loading

  1. hubFrct_2021nakedacosutcicinsgularity hubFrct_2021nakedacosutcicinsgularity Public

    Forked from JQIamo/hubFrct_2021

    Data and Analysis Codes for the Hubble Friction Experiment.

    MATLAB 1

  2. CompositeSpectrum CompositeSpectrum Public

    Forked from hklaufus/CompositeSpectrum

    Python code for creating a composite quasar spectrum from a collection of SDSS quasar spectra.

    Jupyter Notebook

  3. Classification-of-Astronomical-Objects Classification-of-Astronomical-Objects Public

    Forked from alpercakr/Classification-of-Astronomical-Objects

    This project's goal is to classify sky objects such as star, galaxy, and quasar via sdss data.

    Jupyter Notebook

  4. marvin marvin Public

    Forked from sdss/marvin

    Data access and visualization for MaNGA. http://sdss-marvin.readthedocs.io/en/latest/

    Python

  5. SDSS-EPO SDSS-EPO Public

    Forked from brittlundgren/SDSS-EPO

    Educational materials using the Sloan Digital Sky Survey

    Jupyter Notebook

  6. SDSS-VAE SDSS-VAE Public

    Forked from stephenportillo/SDSS-VAE

    Dimensionality Reduction of SDSS Spectra with Variational Autoencoders

    Jupyter Notebook