Costa, Nuno;Zavadlav, Julija
Morphology-Aware Peptide Discovery via Masked Conditional Generative Modeling
ACS Nano
2026

Sanocki, Michał;Zavadlav, Julija
Generalization of Long-Range Machine Learning Potentials in Complex Chemical Spaces
Digital Discovery
2026

Görlich, Franz;Zavadlav, Julija
Mapping Still Matters: Coarse-Graining with Machine Learning Potentials
Journal of Chemical Information and Modeling
2026
66
4

Slejko, Ema;Coste, Amaury;Potisk, Tilen;Zavadlav, Julija;Praprotnik, Matej
Achieving all-atom molecular dynamics accuracy from the Poisson–Boltzmann method through machine learning
The Journal of Chemical Physics
2026
164
5

Chen, Weilong;Görlich, Franz;Fuchs, Paul;Zavadlav, Julija
Enhanced Sampling for Efficient Learning of Coarse-Grained Machine Learning Potentials
Journal of Chemical Theory and Computation
2025
22
1

Fuchs, Paul;Sanocki, Michał;Zavadlav, Julija
Learning non-local molecular interactions via equivariant local representations and charge equilibration
npj Computational Materials
2025
11
1

Fuchs, Paul;Chen, Weilong;Thaler, Stephan;Zavadlav, Julija
chemtrain-deploy: A Parallel and Scalable Framework for Machine Learning Potentials in Million-Atom MD Simulations
Journal of Chemical Theory and Computation
2025
21
15
7550-7560

Röcken, Sebastien;Zavadlav, Julija
Enhancing Machine Learning Potentials through Transfer Learning across Chemical Elements
Journal of Chemical Information and Modeling
2025
65
14

Fuchs, Paul;Thaler, Stephan;Röcken, Sebastien;Zavadlav, Julija
chemtrain: Learning deep potential models via automatic differentiation and statistical physics
Computer Physics Communications
2025
310
109512

Röcken, Sebastien;Burnet, Anton F.;Zavadlav, Julija
Predicting solvation free energies with an implicit solvent machine learning potential
The Journal of Chemical Physics
2024
161
23