6 papers
Sparse Configuration Interaction for the Electronic Schrödinger Equation Revisited: Complete Basis Set Limit Complexity and Quantum-Encoding Impact
Michael Griebel, Jan Hamaekers
In this article we revisit regularity results for eigenfunctions in the discrete spectrum of the electronic Schrödinger equation and study their consequences for approximation com…
Gaussian Process Regression-based Knowledge Distillation Framework for Simultaneous Prediction of Physical and Mechanical Properties of Epoxy Polymers
Sindu B. S., Jan Hamaekers
Epoxy polymers are widely used due to their multifunctional properties, but machine learning (ML) applications remain limited owing to their complex 3D molecular structure, multi-c…
Flexible Cutoff Learning: Optimizing Machine Learning Potentials After Training
Rick Oerder, Jan Hamaekers
We introduce Flexible Cutoff Learning (FCL), a method for training machine learning interatomic potentials (MLIPs) whose cutoff radii can be adjusted after training. Unlike convent…
Materium: An Autoregressive Approach for Material Generation
Niklas Dobberstein, Jan Hamaekers
We present Materium: an autoregressive transformer for generating crystal structures that converts 3D material representations into token sequences. These sequences include element…
On Multilevel Energy-Based Fragmentation Methods
James Barker, Michael Griebel, Jan Hamaekers
Energy-based fragmentation methods approximate the potential energy of a molecular system as a sum of contribution terms built from the energies of particular subsystems. Some such…
Feature-based prediction of properties of cross-linked epoxy polymers by molecular dynamics and machine learning techniques
Sindu B. S., Jan Hamaekers
Epoxy polymers are used in wide range of applications. The properties and performance of epoxy polymers depend upon various factors like the type of constituents and their proporti…