iqspr

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

isqpr is an R package to find candidate molecules that has your desired chemical structures and chemical properties. SMILES (Simplified Molecular Input Line Entry Specification Syntax) is employed to represent chemical structures. To find candidate molecules, sequential Monte Carlo method generates  new molecules, whose chemical properties are predicted by machine learning techniques.

To Detail

aenet (ænet, The Atomic Energy Network)

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

aenet is software for atomic interaction potentials using artificial neural networks. Users can construct neural network potentials using structures of target materials and their energies obtained from first principle calculations. The generated potentials can be used to molecular dynamics or Monte Carlo simulations.

To Detail

QuCumber

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

QuCumber is an open-source Python package that implements neural-network quantum state reconstruction of many-body wavefunctions from measurement data such as magnetic spin projections, orbital occupation number. Given a training dataset of measurements, QuCumber discovers the most likely quantum state compatible with the measurements by finding the optimal set of parameters of a restricted Boltzmann machine (RBM).

.

To Detail

PHYSBO (optimization tools for PHYsics based on Bayesian Optimization )

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

PHYSBO is a Python library for researchers mainly in the materials science field to perform fast and scalable Bayesian optimization based on COMBO (Common Bayesian Optimization). Users can search the candidate with the largest objective function value from candidates listed in advance by using machine learning prediction. PHYSBO can handle a larger amount of data compared with standard implementations such as scikit-learn.

To Detail

2DMAT

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

2DMAT is a framework for applying a search algorithm to a direct problem solver to find the optimal solution. In  version 1.0, for solving a direct problem, 2DMAT offers the wrapper of the solver for the total-reflection high-energy positron diffraction (TRHEPD) experiment. As algorithms, it offers the Nelder-Mead method, the grid search method, the Bayesian optimization method, and the replica exchange Monte Carlo method. Users can define original direct problem solvers or the search algorithms.

To Detail

Chainer

  • Level of openness 3 ★★★
  • Document quality 3 ★★★

An open-source library for machine learning. Various functions on machine learning/deep learning are implemented in this package. Using flexible user-friendly description, various types of networks from simple to complex ones can be implemented. GPGPU parallel computation based on CUDA is also supported.

To Detail

Strawberry Fields

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

Python library for the design, simulation, and optimization of continuous-variable quantum optical circuits. It has high-level functions for solving problems including graph and network optimization, machine learning, and chemistry, and can perform training and optimization of quantum programs using the TensorFlow backend.

To Detail

Caffe

  • Level of openness 3 ★★★
  • Document quality 3 ★★★

An open-source library for machine learning. Various functions on deep learning based on neural network can be used by this package. This package is especially customised for image identification, and a number of sample codes are prepared. Users can also use pre-trained models, which are open in Caffe Model Zoo. Since this package is written in C++, high-speed operation is realised.

To Detail

EVO

  • Level of openness 3 ★★★
  • Document quality 1 ★☆☆

An application for structure prediction based on the evolutionary algorithm. From an input of the atomic position in a unit cell and possible elements at each atomic position, this application predicts the stable structure and composition from the first-principles calculation and molecular dynamics in combination with the evolutionary algorithm. This application is written in Python, and uses Quantum ESPRESSO and GULP as an external program.

To Detail

scikit-learn

  • Level of openness 3 ★★★
  • Document quality 3 ★★★

An open-source library for data mining and data analysis. This package implements various methods of machine learning such as supervised learning (data classification, data regression, etc.), unsupervised learning (data clustering, etc.), and data pre-processing. This package is implemented on Python numerical libraries, NumPy and Scipy, and supports parallel computation.

To Detail