Maps on probability measures preserving certain distances - a survey and some new results
D. Virosztek, Acta Scientiarum Mathematicarum 84 (2018) 65–80.

Quantum interference in laser spectroscopy of highly charged lithiumlike ions
P. Amaro, U. Loureiro, L. Safari, F. Fratini, P. Indelicato, T. Stöhlker, J. Santos,  Physical Review A - Atomic, Molecular, and Optical Physics 97 (2018).

An introduction to the maximum entropy approach and its application to inference problems in biology
A. De Martino, D. De Martino, Heliyon 4 (2018).

Two-photon processes based on quantum commutators
F. Fratini, L. Safari, P. Amaro, J. Santos, Physical Review A - Atomic, Molecular, and Optical Physics 97 (2018).

Fabrication and operation of microfluidic hanging drop networks
P. Misun, A. Birchler, M. Lang, A. Hierlemann, O. Frey, Methods in Molecular Biology 1771 (2018) 183–202.

Learning equations for extrapolation and control
S. Sahoo, C. Lampert, G.S. Martius, in:, Proceedings of the 35th International Conference on Machine Learning, ML Research Press, 2018, pp. 4442–4450.

Counting blanks in polygonal arrangements
A. Akopyan, E. Segal Halevi, SIAM Journal on Discrete Mathematics 32 (2018) 2242–2257.

3-Webs generated by confocal conics and circles
A. Akopyan, Geometriae Dedicata 194 (2018) 55–64.

Persistence of translational symmetry in the BCS model with radial pair interaction
A. Deuchert, A. Geisinge, C. Hainzl, M. Loss, Annales Henri Poincare 19 (2018) 1507–1527.

Near-optimal self-stabilising counting and firing squads
C. Lenzen, J. Rybicki, Distributed Computing (2018).

Drag enhancement and drag reduction in viscoelastic flow
A. Varshney, V. Steinberg, Physical Review Fluids 3 (2018).

Mixing layer instability and vorticity amplification in a creeping viscoelastic flow
A. Varshney, V. Steinberg, Physical Review Fluids 3 (2018).

Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images
A. Kolesnikov, Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images, Institute of Science and Technology Austria, 2018.

Learning from dependent data
A. Zimin, Learning from Dependent Data, Institute of Science and Technology Austria, 2018.

Data-dependent stability of stochastic gradient descent
I. Kuzborskij, C. Lampert, in:, Proceedings of the 35 Th International Conference on Machine Learning, ML Research Press, 2018, pp. 2815–2824.

Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering
T. Ellis, D. Field, N.H. Barton, Molecular Ecology Resources 18 (2018) 988–999.

Data and Python scripts supporting Python package FAPS
T. Ellis, (2018).

Establishment in a new habitat by polygenic adaptation
N.H. Barton, A. Etheridge, Theoretical Population Biology 122 (2018) 110–127.

Learning three-dimensional flow for interactive aerodynamic design
N. Umetani, B. Bickel, ACM Trans. Graph. 37 (2018).

Computational design of nanostructural color for additive manufacturing
T. Auzinger, W. Heidrich, B. Bickel, ACM Transactions on Graphics 37 (2018).