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Albert Musaelian
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2020 – today
- 2024
- [i7]Xiang Fu, Andrew S. Rosen, Kyle Bystrom, Rui Wang, Albert Musaelian, Boris Kozinsky, Tess E. Smidt, Tommi S. Jaakkola:
A Recipe for Charge Density Prediction. CoRR abs/2405.19276 (2024) - 2023
- [c1]Boris Kozinsky
, Albert Musaelian
Scaling the Leading Accuracy of Deep Equivariant Models to Biomolecular Simulations of Realistic Size. SC 2023: 2:1-2:12 - [i6]Albert Musaelian, Anders Johansson, Simon L. Batzner, Boris Kozinsky:
Scaling the leading accuracy of deep equivariant models to biomolecular simulations of realistic size. CoRR abs/2304.10061 (2023) - [i5]Mgcini Keith Phuthi, Archie Mingze Yao, Simon L. Batzner, Albert Musaelian, Boris Kozinsky, Ekin Dogus Cubuk, Venkatasubramanian Viswanathan:
Accurate Surface and Finite Temperature Bulk Properties of Lithium Metal at Large Scales using Machine Learning Interaction Potentials. CoRR abs/2305.06925 (2023) - [i4]Xiang Fu, Albert Musaelian, Anders Johansson, Tommi S. Jaakkola, Boris Kozinsky:
Learning Interatomic Potentials at Multiple Scales. CoRR abs/2310.13756 (2023) - 2022
- [i3]Albert Musaelian, Simon L. Batzner, Anders Johansson, Lixin Sun, Cameron J. Owen, Mordechai Kornbluth, Boris Kozinsky:
Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics. CoRR abs/2204.05249 (2022) - [i2]Ilyes Batatia, Simon L. Batzner, Dávid Péter Kovács, Albert Musaelian, Gregor N. C. Simm, Ralf Drautz, Christoph Ortner, Boris Kozinsky, Gábor Csányi:
The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials. CoRR abs/2205.06643 (2022) - [i1]Albert Zhu, Simon L. Batzner, Albert Musaelian, Boris Kozinsky:
Fast Uncertainty Estimates in Deep Learning Interatomic Potentials. CoRR abs/2211.09866 (2022)
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