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Home › Posts tagged delta-learning

Tag: delta-learning

Chapter on Machine Learning in Quantum Chemistry in a Tutorial Way

By Pavlo Dral Posted on September 22, 2020 Posted in Machine Learning in Chemistry, News No Comments Tagged with book chapter, delta-learning, ML, MLatom, nonadiabatic dynamics, publications, SQC, tutorial

My book chapter shows in a tutorial way how to use machine learning to assist quantum chemistry research.

hML: Hierarchical Machine Learning for PESs

By Pavlo Dral Posted on May 28, 2020 Posted in Machine Learning in Chemistry No Comments Tagged with delta-learning, hML, J. Chem. Phys., ML, MLatom, publications

We introduced hierarchical machine learning (hML) approach for building highly accurate potential energy surfaces from multiple Δ-ML models, each trained on semi-automatically defined training points.

News & Posts

  • MLatom 3: 10-year anniversary edition is released! September 22, 2023
  • Energy-conserving molecular dynamics is not energy conserving! August 25, 2023
  • Beyond 3D-Machine Learning Interatomic Potentials: Meet 4D-Spacetime Atomistic Artificial Intelligence Models August 24, 2023
  • Chapter “Machine Learning Methods in Photochemistry and Photophysics” August 21, 2023
  • QD3SET-1: A Database with Quantum Dissipative Dynamics Data Sets August 10, 2023

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