GitPlanet

Cheap and reliable Node.js hosting starts at $3/month, and $1/month static HTML hosting

Created with love in Canada, visit hostnodejs.com today

Feel like to post an Ad? Learn Details
All Projects → juanjosegarciaripoll → Seemps

juanjosegarciaripoll / Seemps

Licence: mit
Self-explaining Matrix Product States library in Python

Labels

jupyter-notebook

Projects that are alternatives of or similar to Seemps

Av got deeplearning
AV datahack on deep learning CV
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
Behavioral Cloning Hacktorial
All the files needed for the Terrapin Hackers Hacktorial on Behavioral Cloning for Self Driving Cars.
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
Ml Sims
Machine Learning applied to Cosmological Simulations
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
Cos 2019
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
Econ 101b
Macroeconomics
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
Traffic Sign Classifier
Udacity Self-Driving Car Engineer Nanodegree. Project: Build a Traffic Sign Recognition Classifier
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
Cvpr2015
Stars: ✭ 867 (+6569.23%)
Mutual labels:  jupyter-notebook
Ml portofolio
This repo will contain my machine learning projects.
Stars: ✭ 13 (+0%)
Mutual labels:  jupyter-notebook
Neural Image Captioning
Implementation of Neural Image Captioning model using Keras with Theano backend
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
Nla2015
The main github repository for NLA2015 course
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
Sc2ai
Integrated Tensorforce and OpenAI Gym to train SC II game agents.
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
Coursera Ml Andrewng
use numpy, scipy, and tensorflow to implement these basic ML model and learning algorithm
Stars: ✭ 869 (+6584.62%)
Mutual labels:  jupyter-notebook
Notebooks
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
Nltweets
"Our corpus is tweets."
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
Ridge Directed Ring Detector
Robust and highly performant ring detection algorithm for 3d particle tracking using 2d microscope imaging
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
Peyotl
python library for interacting with Open Tree of Life resources
Stars: ✭ 11 (-15.38%)
Mutual labels:  jupyter-notebook
Atari
1-step Q Learning from the paper "Asynchronous Methods for Deep Reinforcement Learning"
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
Ganocracy
Stars: ✭ 13 (+0%)
Mutual labels:  jupyter-notebook
Disease Detection Using Xray
Stars: ✭ 13 (+0%)
Mutual labels:  jupyter-notebook
Mozfest15 Training
Notebooks for Jupyter training session at Mozfest 2015
Stars: ✭ 12 (-7.69%)
Mutual labels:  jupyter-notebook
View All Similar Projects ➔

SeeMPS

Introduction

SEEMPS is the SElf-Explaining Matrix-Product-State library.

It is a collection of Jupyter notebooks that literary programming Python implementation of Matrix-Product-State algorithms. The notebooks combine brief explanations of the algorithms and the details of the implementations. We have chosen the most essential algorithms in their simplest form, so as to provide a gentle introduction to the field.

The library is thought out as introduction to the world of Matrix Product States and DMRG-inspired algorithms. Its main goal is not performance, but rapid prototyping and testing of ideas, providing a good playground before dwelling in more advanced (C++, Julia) versions of the algorithms.

Requirements

The library is entirely developed in Python 3 using Numpy and Scipy, and a standard Jupyter environment. We recommend using Anaconda3 or Miniconda3, although any other distribution of Python should suffice.

Version: 0.0

Authors:

  • Burçin Danaci (Istanbul Technical University)
  • Juan José García Ripoll (Institute of Fundamental Physics)
Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].