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Citrine Tools for Materials Informatics
Tools | 05 Dec 2019 | Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan
Jupyter notebooks for sequential learning in the context of materials design. Run your own models, explore various methods and adapt the notebooks to your needs.
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Entanglement, Inc - revolutionizing computation | transforming ai
Online Presentations | 06 Nov 2019 | Contributor(s):: Jason Turner
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Universal Variational Quantum Computation
Online Presentations | 28 Oct 2019 | Contributor(s):: Jacob Biamonte
We show that the variational approach to quantum enhanced algorithms admits a universal model of quantum computation.
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Machine Learning for Quantum Control
Online Presentations | 28 Oct 2019 | Contributor(s):: Barry Sanders
We develop a framework that connects reinforcement learning with classical and quantum control, and this framework yields adaptive quantum-control policies that beat the standard quantum limit, inspires new methods for improving quantum-gate design for quantum computing, and suggest new ways to...
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Barry Sanders
Dr. Barry Sanders is Director of the Institute for Quantum Science and Technology at the Univer- sity of Calgary, Lead Investigator of the Alberta Major Innovation Fund Project on Quantum Tech-...
https://nanohub.org/members/269902
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Perspectives on High-Performance Computing in a Big Data World: Part D - Learning Model Details and Agent-Based Simulations
Online Presentations | 17 Oct 2019 | Contributor(s):: Fox, Geoffrey C.
This lecture completes the discussion of MLforHPC. It covers Learning Model Details and Agents and Time-Series Case Studies.
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Perspectives on High-Performance Computing in a Big Data World: Part E - Challenges and Opportunities, Conclusions
Online Presentations | 17 Oct 2019 | Contributor(s):: Fox, Geoffrey C.
This lecture covers the computer science issues raised in this talk. The conclusions note that HPDC/HPC is essential; it is good to work closely with industry with student Internships and Collaborations; the Global AI and Modeling Supercomputer GAIMSC is a good framework with an HPC Cloud linked...
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Perspectives on High-Performance Computing in a Big Data World: Part C - MLaroundHPDC/HPC and MLAutotuning
Online Presentations | 10 Oct 2019 | Contributor(s):: Fox, Geoffrey C.
This is the first part of the discussion of MLforHPC. It includes MLAutotuning (Using ML to configure or autotune ML or HPC simulations and MLaroundHPC (Learning outputs from inputs).
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Perspectives on High-Performance Computing in a Big Data World
Courses | 30 Sep 2019 | Contributor(s):: Fox, Geoffrey C.
This course was deleivered at ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC).High-Performance Computing (HPC) and Cyberinfrastructure have played a leadership role in computational science even since the start of the NSF computing centers program. Thirty...
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Perspectives on High-Performance Computing in a Big Data World: Part B - More on the Evolution of Interests and Communities
Online Presentations | 30 Sep 2019 | Contributor(s):: Fox, Geoffrey C.
This part contains several topics. It discusses the importance of industry in several facets of the field: SysML conference, clouds, MLPerf, the Global AI Supercomputer. The nature of data science and data engineering jobs. We emphasize the need for HPC. We finish by introducing MLforHPC (AI for...
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3 min Research Talk: Web-based Machine Learning Tool for Material Discovery and Property Prediction
Online Presentations | 26 Sep 2019 | Contributor(s):: Bryan Arciniega
This model allows the end-user to increase their knowledge on a scarce data set by using a data-rich property set. We also investigate the effect of chemical representation and autoencoder type on property prediction and compound generation.
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3 min Research Talk: Using Machine Learning for Materials Discovery and Property Prediction
Online Presentations | 26 Sep 2019 | Contributor(s):: Mackinzie S Farnell
Machine Learning models present a transformative method of optimization and prediction in science and engineering research. In the chemical sciences, unsupervised deep learning models such as autoencoders have shown to be useful for property prediction and material...
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Mehedi Hossen Limon
https://nanohub.org/members/265976
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Machine Learning for Property Prediction and Materials Discovery
Presentation Materials | 20 Sep 2019 | Contributor(s):: Mackinzie S Farnell, Nicolae C Iovanac, Brett Matthew Savoie
Machine learning displays excellent potential for generating material property predictions and discovering novel compounds with desirable properties; however, it can be prohibitively costly to obtain data to train machine learning models. This barrier can be overcome by training models to...
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Chemical Autoencoder for Latent Space Enrichment
Tools | 19 Sep 2019 | Contributor(s):: Bryan Arciniega, Mackinzie S Farnell, Nicolae C Iovanac, Brett Matthew Savoie
Chemical Autencoder uses machine learning for property prediction
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Data Science and Machine Learning for MSE Students: introduction and Hands-on Activities
Teaching Materials | 10 Sep 2019 | Contributor(s):: Alejandro Strachan, Juan Carlos Verduzco Gastelum, Saaketh Desai
This document introduces basic concepts of data science and machine learning in the context of materials science applications. The focus is on hands-on activities where readers use open, online tools in nanoHUB to explore the concepts being introduced. Topics covered include querying data...
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Web-based Machine Learning Tool for Material Discovery and Property Prediction
Presentation Materials | 20 Aug 2019 | Contributor(s):: Bryan Arciniega, Mackinzie S Farnell, Nicolae C Iovanac, Brett Matthew Savoie
Machine Learning models present a transformative method of optimization and prediction in science and engineering research. In the chemical sciences, unsupervised deep learning models such as autoencoders have shown to be useful for property prediction and material...
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Quantum Information and Computation for Quantum Chemistry
Online Presentations | 14 Aug 2019 | Contributor(s):: Sabre Kais
Recently, Purdue University received $1.5 million in National Science Foundation (NSF) funding to establish a research center to study quantum information science. The Center for Quantum Information and Computation for Chemistry will investigate information techniques used to gain novel...
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Perspectives on High-Performance Computing in a Big Data World: Part A - Data on the Evolution of Interests and Communities
Online Presentations | 13 Aug 2019 | Contributor(s):: Fox, Geoffrey C.
This lecture has an overall outline of the 5 part presentation. It covers trends seen from conferences and journals -- the number of papers, attendees and h5index. Then we look at relevant Google Trends. Cyberinfrastructure related activities are less buoyant than those for AI and ML.
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Introduction to Deep Reinforcement Learning
Online Presentations | 03 Jul 2019 | Contributor(s):: Balaraman Ravindran
Reinforcement learning is a paradigm that aims to model the trial-and-error learning process that is needed in many problem situations where explicit instructive signals are not available. It has roots in operations research, behavioural psychology and AI. ...