Philip Loche
- Fast and flexible long-range models for atomistic machine learning
2024/12/04 by Philip Loche, Loche, Philip, Kevin K. Huguenin-Dumittan +13 · 1 voice · 10 citations
#physics.chem-ph
- Energy Transfer within the Hydrogen Bonding Network of Water Following\n Resonant Terahertz Excitation
2020/03/19 by Hossam Elgabarty, Tobias Kampfrath, Elgabarty, Hossam +17 · 3 citations
Physics and Astronomy · Engineering · #Spectroscopy and Quantum Chemical Studies #Terahertz technology and applications #Mechanical and Optical Resonators
- Physics-inspired Equivariant Descriptors of Non-bonded Interactions
2023/08/25 by Kevin K. Huguenin-Dumittan, Philip Loche, Huguenin-Dumittan, Kevin K. +5 · 4 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · #Chemical Physics (physics.chem-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Protein Structure and Dynamics #Topic Modeling
- Dielectric properties of aqueous electrolytes at the nanoscale
2023/03/26 by Maximilian R. Becker, Becker, Maximilian R., Philip Loche +9 · 3 citations
Chemistry · Engineering · Physics and Astronomy · #Electrostatics and Colloid Interactions #FOS: Physical sciences #Nanopore and Nanochannel Transport Studies #Soft Condensed Matter (cond-mat.soft) #Spectroscopy and Quantum Chemical Studies
- Metatensor and metatomic: foundational libraries for interoperable atomistic machine learning
2025/08/21 by Filippo Bigi, Joseph W. Abbott, Bigi, Filippo +27 · 1 voice · 5 citations
#physics.chem-ph
- Learning Long-Range Representations with Equivariant Messages
2025/07/25 by Egor Rumiantsev, Marcel F. Langer, Rumiantsev, Egor +7 · 2 citations
Computer Science · Materials Science · Physics and Astronomy · #Advanced Graph Neural Networks #Chemical Physics (physics.chem-ph) #FOS: Physical sciences #Machine Learning in Materials Science #Quantum many-body systems