June 21, 2018 UMD Home FabLab AIMLab
MLMR 2018
Machine Learning for Materials Research
Workshop on Machine Learning Quantum Materials
July 30, 2018 - August 3, 2018

Last updated: June 11, 2018, 10:34 pm EDT

Monday, July 30th

Tutorial on Python & Data Fundamentals and Preprocessing

Alex Belianinov (ORNL) and Brian DeCost (NIST)

  • Filtering: Noise Smoothing
  • Background Subtraction
  • Feature Extraction
    • Cross-correlation Wavelets
    • Edges
    • Closed Boundaries
    • Shapes

Evening Reception

Tuesday, July 31st

Unsupervised Machine Learning

A. Gilad Kusne (NIST)

  • Theory
  • Similarity Measures
  • Latent Variable Analysis
  • Spectral Unmixing
  • Matrix Factorization
  • Clustering

Hackathon Start

Wednesday, August 1st

Supervised Machine Learning

Dan Samarov (NIST)

  • Data Handling
    • Cross Validation
    • Prediction
  • Algorithms
    • Regularized Least Squared
    • Support Vector Machines
    • Neural Networks
    • Decision Trees & Ensemble Learning
    • Genetic Programming

Evening Poster Session

We will have our annual Poster Session Wednesday Evening titled: Machine Learn This. Please bring a poster on your work on machine learning or on your favorite data for which we will discuss machine learning approaches. Please indicate if you are planning to bring a poster when you register.

Thursday, August 2nd

Machine Learning on DFT and Experimental Databases

Dane Morgan (U. of Wisconsin)

  • Introduction to DFT
  • Machine Learning of DFT Based Data

Kamal Choudhary (NIST)

  • JARVIS-ML: 2D/3D materials screening and genetic algorithm with ML model

Valentin Stanev (U. of Maryland)

  • Machine Learning of Experimental Databases: Case Study on Superconductivity

Cormac Toher, Corey Oses, and David Hicks (Duke U.)

  • Tutorial on AFLOW


Friday, August 3rd

Workshop on Machine Learning Quantum Materials

Organized by Johnpierre Paglione (U. of Maryland) and Ichiro Takeuchi (U. of Maryland)

Confirmed Invited speakers

Antoine Georges (Center for Computational Quantum Physics)
Karin Rabe (Rutgers)
Sasha Balatsky (LANL/Nordita)
Andy Millis (Columbia)
Roger Melko (Waterloo)
Shoucheng Zhang (Stanford)
Mike Norman (ANL)

Experimental Approaches

Ichiro Takeuchi (UMD)
Sergei Kalinin (ORNL)
Benji Maruyama (AFRL)
Jiun-Haw Chu (Univ. Washington)

Computational Approaches

Stefano Curtarolo (Duke)
Gus Hart (BYU)
Giuseppe Carleo (Flatiron)
Miles Soudenmire (Flatiron)

Conference Support

Colleges A. James Clark School of Engineering
The College of Computer, Mathematical, and Natural Sciences

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