All Categories (1-11 of 11)

1. Accelerating Radiation Damage Simulation Through Machine Learning

   Online Presentations | 21 May 2024 | Contributor(s):: Vinay Gupta, Shrienidhi Gopalakrishnan, Brian Hyun-jong Lee, Alejandro Strachan

   This study explores the challenge of material degradation from radiation exposure, a phenomenon that significantly impacts fields ranging from materials science to nuclear engineering and space exploration. As of today, the primary solution of conventional simulation techniques are...

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   Kutand Alkım Bayer

   https://nanohub.org/members/394875

3. GPU Implementation of MXMNet

   Tools | 01 Jun 2022 | Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan

   GPU Implementation of MXMNet

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   Mayank Agrawal

   https://nanohub.org/members/354771

5. A Hands-on Introduction to Physics-Informed Neural Networks

   Online Presentations | 16 Jun 2021 | Contributor(s):: Ilias Bilionis, Atharva Hans

   Can you make a neural network satisfy a physical law? There are two main types of these laws: symmetries and ordinary/partial differential equations. I will focus on differential equations in this short presentation. The simplest way to bake information about a differential equation with neural...

6. A Hands-on Introduction to Physics-Informed Neural Networks

   Tools | 21 May 2021 | Contributor(s):: Atharva Hans, Ilias Bilionis

   A Hands-on Introduction to Physics-Informed Neural Networks

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   Evren Toptop

   https://nanohub.org/members/303331

8. Parsimonious neural networks

   Tools | 09 Jul 2020 | Contributor(s):: Saaketh Desai, Alejandro Strachan

   Design and train neural networks in conjunction with genetic algorithms to discover equations directly from data

9. Parsimonious Neural Networks Learn Classical Mechanics and Can Teach It

   Papers | 15 May 2020 | Contributor(s):: Saaketh Desai, Alejandro Strachan

   We combine neural networks with genetic algorithms to find parsimonious models that describe the time evolution of a point particle subjected to an external potential. The genetic algorithm is designed to find the simplest, most interpretable network compatible with the training data. The...

10. ECE 695E: An Introduction to Data Analysis, Design of Experiment, and Machine Learning

    Courses | 07 Jan 2019 | Contributor(s):: Muhammad A. Alam

    This course will provide the conceptual foundation so that a student can use modern statistical concepts and tools to analyze data generated by experiments or numerical simulation.

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    Abdelaali Fargi

    Abdelaali Fargi received his PhD in Physics of Semiconductor Devices and Electronics from Faculty of Sciences of Monastir (Tunisia) in 2016, the Master of Science Degree in Materials Science and...

    https://nanohub.org/members/56303