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APS symposium: Machine Learning for Electronic S ... (No replies)

pavanell
1 year ago
pavanell 1 year ago

Deadline is approaching for submitting contributed abstracts!

Abstract submission details are available at https://march.aps.org/ with deadline October 20.

The sorting category is: 16.01.04 Machine Learning for Electronic Structure, Properties, and Dynamics of Molecules and Materials

Our distinguished invited speakers include: Michele Ceriotti, Pavlo Dral, Rafael Gómez-Bombarelli, Christine Isborn, Heather Kulik, Klaus-Robert Müller, and Anatole von Lilienfeld

Key Topics Include:

  • Advancements in Quantum Machine Learning
  • ML-Based Density Functionals for DFT Simulations
  • Machine Learning in Ab-initio Dynamics
  • Prospects and Challenges of Current ML Models

We look forward to seeing you in Minneapolis!




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Ab initio (from electronic structure) calculation of complex processes in materials