Ilyes Batatia - RankMe

25 papers A* 4A 1Misc 1Journal 17Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Design Space of Self-Consistent Electrostatic Machine Learning Interatomic Potentials. CoRR William J. Baldwin, Ilyes Batatia, Martin Vondrák, Johannes T. Margraf, Gábor Csányi
2026	J	`jnl`	MACE-POLAR-1: A Polarisable Electrostatic Foundation Model for Molecular Chemistry. CoRR Ilyes Batatia, William J. Baldwin, Domantas Kuryla, Joseph Hart, Elliott Kasoar, Alin M. Elena, Harry Moore, Mikolaj J. Gawkowski, Benjamin X. Shi, Venkat Kapil, Panagiotis Kourtis, Ioan-Bogdan Magdau, Gábor Csányi
2025	A	`conf`	Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE. HPDC Jesun Sahariar Firoz, Franco Pellegrini, Mario Geiger, Darren Hsu, Jenna A. Bilbrey, Han-Yi Chou, Maximilian Stadler, Markus Höhnerbach, Tingyu Wang, Dejun Lin, Emine Küçükbenli, Henry W. Sprueill, Ilyes Batatia, Sotiris S. Xantheas, MalSoon Lee, Christopher J. Mundy, Gábor Csányi, Justin S. Smith, Ponnuswamy Sadayappan, Sutanay Choudhury
2025	J	`jnl`	Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE. CoRR 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, Ilyes Batatia, Sotiris S. Xantheas, MalSoon Lee, Chris Mundy, Gábor Csányi, Justin S. Smith, Ponnuswamy Sadayappan, Sutanay Choudhury
2025	J	`jnl`	The design space of E(3)-equivariant atom-centred interatomic potentials. Nat. Mac. Intell. Ilyes Batatia, Simon L. Batzner, Dávid Péter Kovács, Albert Musaelian, Gregor N. C. Simm, Ralf Drautz, Christoph Ortner, Boris Kozinsky, Gábor Csányi
2024	J	`jnl`	Benchmarking of machine learning interatomic potentials for reactive hydrogen dynamics at metal surfaces. Mach. Learn. Sci. Technol. Wojciech G. Stark, Cas van der Oord, Ilyes Batatia, Yaolong Zhang, Bin Jiang, Gábor Csányi, Reinhard Johann Maurer
2024	J	`jnl`	BoostMD: Accelerating molecular sampling by leveraging ML force field features from previous time-steps. CoRR Lars L. Schaaf, Ilyes Batatia, Christoph Brunken, Thomas D. Barrett, Jules Tilly
2024	A*	`conf`	Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials. ICLR Ivan Grega, Ilyes Batatia, Gábor Csányi, Sri Karlapati, Vikram S. Deshpande
2024	J	`jnl`	Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials. CoRR Ivan Grega, Ilyes Batatia, Gábor Csányi, Sri Karlapati, Vikram S. Deshpande
2024	A*	`conf`	Equivariant Matrix Function Neural Networks. ICLR Ilyes Batatia, Lars L. Schaaf, Gábor Csányi, Christoph Ortner, Felix A. Faber
2024	Misc	`conf`	QUACE: Symmetrized Molecular Descriptors on a Quantum Circuit. QCE Lila Cadi Tazi, Ilyes Batatia, Alex J. W. Thom, Gábor Csánvi
2024	J	`jnl`	Zero Shot Molecular Generation via Similarity Kernels. CoRR Rokas Elijosius, Fabian Zills, Ilyes Batatia, Sam Walton Norwood, Dávid Péter Kovács, Christian Holm, Gábor Csányi
2023	A*	`conf`	A General Framework for Equivariant Neural Networks on Reductive Lie Groups. NeurIPS Ilyes Batatia, Mario Geiger, Jose M. Munoz, Tess E. Smidt, Lior Silberman, Christoph Ortner
2023	J	`jnl`	A General Framework for Equivariant Neural Networks on Reductive Lie Groups. CoRR Ilyes Batatia, Mario Geiger, Jose M. Munoz, Tess E. Smidt, Lior Silberman, Christoph Ortner
2023	—	`conf`	A Geometric Insight into Equivariant Message Passing Neural Networks on Riemannian Manifolds. TAG-ML Ilyes Batatia
2023	J	`jnl`	A Geometric Insight into Equivariant Message Passing Neural Networks on Riemannian Manifolds. CoRR Ilyes Batatia
2023	J	`jnl`	Equivariant Matrix Function Neural Networks. CoRR Ilyes Batatia, Lars L. Schaaf, Huajie Chen, Gábor Csányi, Christoph Ortner, Felix A. Faber
2023	J	`jnl`	Retrieval of Boost Invariant Symbolic Observables via Feature Importance. CoRR Jose M. Munoz, Ilyes Batatia, Christoph Ortner, Francesco Romeo
2022	J	`jnl`	BIP: Boost Invariant Polynomials for Efficient Jet Tagging. CoRR Jose M. Munoz, Ilyes Batatia, Christoph Ortner
2022	J	`jnl`	Boost invariant polynomials for efficient jet tagging. Mach. Learn. Sci. Technol. Jose M. Munoz, Ilyes Batatia, Christoph Ortner
2022	A*	`conf`	MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields. NeurIPS Ilyes Batatia, Dávid Péter Kovács, Gregor N. C. Simm, Christoph Ortner, Gábor Csányi
2022	J	`jnl`	MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields. CoRR Ilyes Batatia, Dávid Péter Kovács, Gregor N. C. Simm, Christoph Ortner, Gábor Csányi
2022	J	`jnl`	Tensor-reduced atomic density representations. CoRR James P. Darby, Dávid Péter Kovács, Ilyes Batatia, Miguel A. Caro, Gus L. W. Hart, Christoph Ortner, Gábor Csányi
2022	J	`jnl`	The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials. CoRR Ilyes Batatia, Simon L. Batzner, Dávid Péter Kovács, Albert Musaelian, Gregor N. C. Simm, Ralf Drautz, Christoph Ortner, Boris Kozinsky, Gábor Csányi
2020	—	`conf`	A Deep Learning Method with CRF for Instance Segmentation of Metal-Organic Frameworks in Scanning Electron Microscopy Images. EUSIPCO Ilyes Batatia