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Fabian Zills

Showing results (1-10 of 9) with videos related to

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Journal of Chemical Theory and Computation|December 9, 2021
Thermally Averaged Magnetic Anisotropy Tensors via Machine Learning Based on Gaussian MomentsViktor Zaverkin, Julia Netz, Fabian Zills, et al.
Faraday Discussions|July 26, 2024
Machine learning-driven investigation of the structure and dynamics of the BMIM-BF<sub>4</sub> room temperature ionic liquidFabian Zills, Moritz René Schäfer, Samuel Tovey, et al.
Journal of Chemical Information and Modeling|July 30, 2025
Apax: A Flexible and Performant Framework for the Development of Machine-Learned Interatomic PotentialsMoritz R Schäfer, Nico Segreto, Fabian Zills, et al.
Journal of Cheminformatics|February 11, 2023
MDSuite: comprehensive post-processing tool for particle simulationsSamuel Tovey, Fabian Zills, Francisco Torres-Herrador, et al.
The Journal of Physical Chemistry. B|April 3, 2024
Collaboration on Machine-Learned Potentials with IPSuite: A Modular Framework for Learning-on-the-FlyFabian Zills, Moritz René Schäfer, Nico Segreto, et al.
Nature Communications|July 2, 2025
Zero shot molecular generation via similarity kernelsRokas Elijošius, Fabian Zills, Ilyes Batatia, et al.
Journal of Physics. Condensed Matter : an Institute of Physics Journal|August 29, 2025
MLIPX: Machine Learned Interatomic Potential eXplorationFabian Zills, Sheena Agarwal, Tiago Goncalves, et al.
Faraday Discussions|October 7, 2024
Structure and dynamics in dense ionic fluids: general discussionAndrew P Abbott, Rob Atkin, Muhammad Dabai Bala, et al.
The Journal of Chemical Physics|November 13, 2025
A foundation model for atomistic materials chemistryIlyes Batatia, Philipp Benner, Yuan Chiang, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Journal of Chemical Theory and Computation|December 9, 2021
Thermally Averaged Magnetic Anisotropy Tensors via Machine Learning Based on Gaussian MomentsViktor Zaverkin, Julia Netz, Fabian Zills, et al.
Faraday Discussions|July 26, 2024
Machine learning-driven investigation of the structure and dynamics of the BMIM-BF<sub>4</sub> room temperature ionic liquidFabian Zills, Moritz René Schäfer, Samuel Tovey, et al.
Journal of Chemical Information and Modeling|July 30, 2025
Apax: A Flexible and Performant Framework for the Development of Machine-Learned Interatomic PotentialsMoritz R Schäfer, Nico Segreto, Fabian Zills, et al.
Journal of Cheminformatics|February 11, 2023
MDSuite: comprehensive post-processing tool for particle simulationsSamuel Tovey, Fabian Zills, Francisco Torres-Herrador, et al.
The Journal of Physical Chemistry. B|April 3, 2024
Collaboration on Machine-Learned Potentials with IPSuite: A Modular Framework for Learning-on-the-FlyFabian Zills, Moritz René Schäfer, Nico Segreto, et al.
Nature Communications|July 2, 2025
Zero shot molecular generation via similarity kernelsRokas Elijošius, Fabian Zills, Ilyes Batatia, et al.
Journal of Physics. Condensed Matter : an Institute of Physics Journal|August 29, 2025
MLIPX: Machine Learned Interatomic Potential eXplorationFabian Zills, Sheena Agarwal, Tiago Goncalves, et al.
Faraday Discussions|October 7, 2024
Structure and dynamics in dense ionic fluids: general discussionAndrew P Abbott, Rob Atkin, Muhammad Dabai Bala, et al.
The Journal of Chemical Physics|November 13, 2025
A foundation model for atomistic materials chemistryIlyes Batatia, Philipp Benner, Yuan Chiang, et al.
Pageof 1