[go: up one dir, main page]

Skip to content
View cristina-v-melnic's full-sized avatar

Block or report cristina-v-melnic

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
cristina-v-melnic/README.md

Welcome!

  • 👋 Hi there, I’m Cristina @cristina-v-melnic.
  • 💥 I’m currently venturing into advanced topics in data science and machine/deep learning.
  • ✨ I am a huge science enthusiast specialised in physics.
  • 📫 Don't hesitate to contact me at cristina.v.melnic@gmail.com

Projects Portfolio

To find out more about my work, check out the following repos:

Popular repositories Loading

  1. pattern-formation pattern-formation Public

    Modelling pattern formation by numerical integration of systems of coupled convection-diffusion differential equations.

    Python 1

  2. stokes-dg-figures stokes-dg-figures Public

    Analysis of simulation data obtained with the ParMooN finite element package.

    Python

  3. stokes-dg-experiments stokes-dg-experiments Public

    Script that runs experiments on the implemented H(div)-conforming elements for Stokes equations in the finite element package ParMooN.

    C

  4. neural-orientation-tuning neural-orientation-tuning Public

    Model of a single orientation-selective neuron receiving inputs from afferents with different preferred orientations. The project shows what properties the postsynaptic neuron has and how they depe…

    Jupyter Notebook

  5. cristina-v-melnic cristina-v-melnic Public

    Config files for my GitHub profile.

  6. force-inference force-inference Public

    Application to find parameters of inter-particle forces from stochastic trajectories using Bayesian inference.

    Jupyter Notebook