Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics. - Albert Musaelian; Simon L. Batzner; Anders Johansson; Lixin Sun; Cameron J. Owen; Mordechai Kornbluth; Boris Kozinsky (CoRR, 2022)

The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials. - Ilyes Batatia; Simon L. Batzner; Dávid Péter Kovács; Albert Musaelian; Gregor N. C. Simm; Ralf Drautz; Christoph Ortner; Boris Kozinsky; Gábor Csányi (CoRR, 2022)

Fast Uncertainty Estimates in Deep Learning Interatomic Potentials. - Albert Zhu; Simon L. Batzner; Albert Musaelian; Boris Kozinsky (CoRR, 2022)

Scaling the Leading Accuracy of Deep Equivariant Models to Biomolecular Simulations of Realistic Size. - Boris Kozinsky; Albert Musaelian; Anders Johansson; Simon L. Batzner (SC, 2023)

Accurate Surface and Finite Temperature Bulk Properties of Lithium Metal at Large Scales using Machine Learning Interaction Potentials. - Mgcini Keith Phuthi; Archie Mingze Yao; Simon L. Batzner; Albert Musaelian; Boris Kozinsky; Ekin Dogus Cubuk; Venkatasubramanian Viswanathan (CoRR, 2023)

Learning Interatomic Potentials at Multiple Scales. - Xiang Fu 005; Albert Musaelian; Anders Johansson; Tommi S. Jaakkola; Boris Kozinsky (CoRR, 2023)

A Recipe for Charge Density Prediction. - Xiang Fu 005; Andrew S. Rosen; Kyle Bystrom; Rui Wang 086; Albert Musaelian; Boris Kozinsky; Tess E. Smidt; Tommi S. Jaakkola (NeurIPS, 2024)

The design space of E(3)-equivariant atom-centred interatomic potentials. - Ilyes Batatia; Simon L. Batzner; Dávid Péter Kovács; Albert Musaelian; Gregor N. C. Simm; Ralf Drautz; Christoph Ortner; Boris Kozinsky; Gábor Csányi (Nat. Mac. Intell., 2025)

High-performance training and inference for deep equivariant interatomic potentials. - Chuin Wei Tan; Marc L. Descoteaux; Mit Kotak; Gabriel de Miranda Nascimento; Seán R. Kavanagh; Laura Zichi; Menghang Wang; Aadit Saluja; Yizhong R. Hu; Tess E. Smidt; Anders Johansson; William C. Witt; et al. (CoRR, 2025)

Coupled reaction and diffusion governing interface evolution in solid-state batteries. - Jingxuan Ding; Laura Zichi; Matteo Carli; Menghang Wang; Albert Musaelian; Yu Xie; Boris Kozinsky (CoRR, 2025)