Resources (21-40 of 163)

1. ANN Model Generator

   Tools | 11 Jul 2022 | Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan

   Simtool workflow to create ANN models for user datasets

2. Message-Passing Neural Networks for Molecular Property Prediction Using Chemprop

   Online Presentations | 06 May 2022 | Contributor(s):: Kevin Greenman

   Chemprop is an open-source implementation of a directed message passing neural network (D-MPNN) that has been demonstrated to be successful in predicting a variety of molecular properties, including solvation properties, optical properties, infrared spectra, and toxicity....

3. MRS Computational Materials Science Tutorial

   Tools | 04 May 2022 | Contributor(s):: Panayotis Thalis Manganaris, Saaketh Desai, Arun Kumar Mannodi Kanakkithodi

   Hands-on guide to the development of statistical models useful for materials design using python, sklearn, tensorflow, and intel extensions.

4. Optical MNIST dataset

   Downloads | 21 Apr 2022 | Contributor(s):: Hanyu Zheng

   Rapid advances in deep learning have led to paradigm shifts in a number of fields, from medical image analysis to autonomous systems. These advances, however, have resulted in digital neural networks with large computational requirements, resulting in high energy consumption and limitations in...

5. Chemprop Demo

   Tools | 11 Apr 2022 | Contributor(s):: Kevin Greenman

   Demo of the Chemprop message-passing neural network package for the Hands-on Data Science and Machine Learning Training Series

6. Machine Learning with MATLAB

   Online Presentations | 11 Mar 2022 | Contributor(s):: Gaby Arellano Bello

   In this session, we explore the fundamentals of machine learning using MATLAB. We introduce machine learning techniques available in MATLAB to quickly explore your data, evaluate machine learning algorithms, compare the results and apply the best technique to your problem.

7. ML-based Surrogate Models for Nusselt Number and Friction Factor Prediction in Constant Cross-Section Channels

   Tools | 17 Feb 2022 | Contributor(s):: Saeel Shrivallabh Pai, Justin A. Weibel

   Predict laminar fully-developed Nusselt number and friction factor for different cross-section shapes of constant cross-section channels

8. Integrating Machine Learning with a Genetic Algorithm for Materials Exploration

   Online Presentations | 07 Dec 2021 | Contributor(s):: Joseph D Kern

   In this talk, we will explore how this algorithm can be used for materials discovery.

9. Feature Selection for CCA Strength Models

   Tools | 06 Dec 2021 | Contributor(s):: Zachary D McClure, Alejandro Strachan

   A tool to evaluate dataset of hardness and strength values of complex-concentrated-alloys. Feature selection, optimization, and explanation methods are included.

10. Designing Machine Learning Surrogates for Molecular Dynamics Simulations

    Online Presentations | 25 Nov 2021 | Contributor(s):: JCS Kadupitiya

    Molecular dynamics (MD) simulations accelerated by high-performance computing (HPC) methods are powerful tools for investigating and extracting the microscopic mechanisms characterizing the properties of soft materials such as self-assembled nanoparticles, virus capsids, confined electrolytes,...

11. Autonomous Neutron Diffraction Experiments with ANDiE

    Online Presentations | 14 Nov 2021 | Contributor(s):: Austin McDannald

    This tutorial will cover the working principles of ANDiE, how physics was encoded into the design, and demonstrate how ANDiE can be used to autonomously control neutron diffraction experiments.

12. Polymer Genetic Algorithm

    Tools | 05 Nov 2021 | Contributor(s):: Joseph D Kern

    Generalized genetic algorithm designed for materials discovery.

13. Machine Learning in Physics

    Tools | 04 Nov 2021 | Contributor(s):: Nicolas Onofrio

    Lectures and tutorials to learn how to write machine learning programs with Python

14. MatSci 395 Laboratory: Computational Laboratory and Exercises

    Teaching Materials | 03 Nov 2021 | Contributor(s):: Tiberiu Stan

15. Machine Learning in Materials Science: Image Analysis Using Convolutional Neural Networks in MatCNN

    Courses | 03 Nov 2021 | Contributor(s):: Tiberiu Stan, Jim James, Nathan Pruyne, Marcus Schwarting, Jiwon Yeom, Peter Voorhees, Ben J Blaiszik, Ian Foster, Jonathan D Emery

      This course introduces fundamental concepts of artificial intelligence within the context of materials science and image segmentation. The two-week module was taught as part of a Computational Methods in Materials Science course at Northwestern University. The module is aimed at...

16. MatSci 395 Lecture 5: MatCNN In-Class Tutorial

    Online Presentations | 01 Nov 2021 | Contributor(s):: Tiberiu Stan

    Access MatCNN by clicking here

17. MatSci 395 Lecture 6: How Do Convolutional Neural Networks Work?

    Online Presentations | 01 Nov 2021 | Contributor(s):: Tiberiu Stan

18. Autonomous Neutron Diffraction Explorer

    Tools | 01 Nov 2021 | Contributor(s):: Austin McDannald

    Autonomously control neutron diffraction experiments to discover order parameter.

19. Machine learning for high entropy atomic properties

    Tools | 26 Oct 2021 | Contributor(s):: Mackinzie S Farnell, Zachary D McClure, Alejandro Strachan

    Explore machine learning models used to assess the variations in local atomic properties in high entropy alloys.

20. MatSci 395 Lecture 4: Neural Network Training

    Online Presentations | 07 Oct 2021 | Contributor(s):: Tiberiu Stan