A Deep Learning Method with CRF for Instance Segmentation of Metal-Organic Frameworks in Scanning Electron Microscopy Images. - Ilyes Batatia (EUSIPCO, 2020)

MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields. - Ilyes Batatia; Dávid Péter Kovács; Gregor N. C. Simm; Christoph Ortner; Gábor Csányi (NeurIPS, 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)

BIP: Boost Invariant Polynomials for Efficient Jet Tagging. - Jose M. Munoz; Ilyes Batatia; Christoph Ortner (CoRR, 2022)

Tensor-reduced atomic density representations. - James P. Darby; Dávid Péter Kovács; Ilyes Batatia; Miguel A. Caro; Gus L. W. Hart; Christoph Ortner; Gábor Csányi (CoRR, 2022)

Boost invariant polynomials for efficient jet tagging. - Jose M. Munoz; Ilyes Batatia; Christoph Ortner (Mach. Learn. Sci. Technol., 2022)

A General Framework for Equivariant Neural Networks on Reductive Lie Groups. - Ilyes Batatia; Mario Geiger; Jose M. Munoz; Tess E. Smidt; Lior Silberman; Christoph Ortner (NeurIPS, 2023)

A Geometric Insight into Equivariant Message Passing Neural Networks on Riemannian Manifolds. - Ilyes Batatia (TAG-ML, 2023)

Retrieval of Boost Invariant Symbolic Observables via Feature Importance. - Jose M. Munoz; Ilyes Batatia; Christoph Ortner; Francesco Romeo (CoRR, 2023)

Equivariant Matrix Function Neural Networks. - Ilyes Batatia; Lars L. Schaaf; Huajie Chen; Gábor Csányi; Christoph Ortner; Felix A. Faber (CoRR, 2023)

Equivariant Matrix Function Neural Networks. - Ilyes Batatia; Lars L. Schaaf; Gábor Csányi; Christoph Ortner; Felix A. Faber (ICLR, 2024)

Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials. - Ivan Grega; Ilyes Batatia; Gábor Csányi; Sri Karlapati; Vikram S. Deshpande (ICLR, 2024)

QUACE: Symmetrized Molecular Descriptors on a Quantum Circuit. - Lila Cadi Tazi; Ilyes Batatia; Alex J. W. Thom; Gábor Csánvi (QCE, 2024)

Zero Shot Molecular Generation via Similarity Kernels. - Rokas Elijosius; Fabian Zills; Ilyes Batatia; Sam Walton Norwood; Dávid Péter Kovács; Christian Holm; Gábor Csányi (CoRR, 2024)

BoostMD: Accelerating molecular sampling by leveraging ML force field features from previous time-steps. - Lars L. Schaaf; Ilyes Batatia; Christoph Brunken; Thomas D. Barrett; Jules Tilly (CoRR, 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)

Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE. - Jesun Firoz; Franco Pellegrini; Mario Geiger; Darren Hsu; Jenna A. Bilbrey; Han-Yi Chou; Maximilian Stadler; Markus Hoehnerbach; Tingyu Wang; Dejun Lin; Emine Küçükbenli; Henry W. Sprueill; et al. (CoRR, 2025)