Mario Geiger

1. Spherical CNNs
   2018/01/30 by Taco S. Cohen, Mario Geiger, Jonas Koehler +1 · 2 voices · 30 citations
   #cs.LG #stat.ML
2. E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials
   2022/05/04 by Simon Batzner, Albert Musaelian, Lixin Sun +6 · 146 citations
   Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · #Machine Learning in Materials Science #Protein Structure and Dynamics #Topic Modeling
3. e3nn: Euclidean Neural Networks
   2022/07/18 by Mario Geiger, Tess Smidt, Geiger, Mario +1 · 29 citations
   Engineering · Computer Science · #Medical Imaging and Analysis #Neural Networks and Applications #3D Shape Modeling and Analysis
4. SE(3)-equivariant prediction of molecular wavefunctions and electronic\n densities
   2021/06/04 by Oliver T. Unke, Mihail Bogojeski, Unke, Oliver T. +9 · 10 citations
   Biochemistry, Genetics and Molecular Biology · Chemistry · Computer Science · Materials Science · #Chemical Physics (physics.chem-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (stat.ML) #Machine Learning in Materials Science #Protein Structure and Dynamics #Seismology and Earthquake Studies #Topic Modeling #Various Chemistry Research Topics
5. EquiJump: Protein Dynamics Simulation via SO(3)-Equivariant Stochastic Interpolants
   2024/10/12 by Allan dos Santos Costa, Ilan Mitnikov, Costa, Allan dos Santos +17 · 7 citations
   Computer Science · Biochemistry, Genetics and Molecular Biology · Decision Sciences · #Algorithms and Data Compression #Protein Structure and Dynamics #Scientific Computing and Data Management
6. A General Framework for Equivariant Neural Networks on Reductive Lie Groups
   2023/05/31 by Ilyes Batatia, Mario Geiger, Batatia, Ilyes +9 · 3 citations
   Computer Science · Earth and Planetary Sciences · #Computational Physics and Python Applications #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Theory (hep-th) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Seismic Imaging and Inversion Techniques #Seismology and Earthquake Studies
7. BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery
   2024/11/15 by Peter St. John, Peter C. St. John, Dejun Lin +203 · 1 voice · 5 citations
   Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · #Computational Drug Discovery Methods #Genetics, Bioinformatics, and Biomedical Research #Machine Learning in Materials Science #cs.LG #q-bio.BM
8. Phonon predictions with E(3)-equivariant graph neural networks
   2024/03/17 by Shiang Fang, Mario Geiger, Fang, Shiang +5 · 3 citations
   Materials Science · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Thermal properties of materials
9. Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for 3D Molecule Generation
   2023/11/27 by Ameya Daigavane, Daigavane, Ameya, Song Eun Kim +5 · 2 citations
   Biochemistry, Genetics and Molecular Biology · Materials Science · Physics and Astronomy · #Biomolecules (q-bio.BM) #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Protein Structure and Dynamics #Scientific Research and Discoveries
10. Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning
    2023/01/31 by Antonio Sclocchi, Sclocchi, Antonio, Mario Geiger +3 · 1 citation
    Computer Science · Materials Science · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Computer and information sciences #FOS: Physical sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning in Materials Science #Neural Networks and Applications
11. A fast summation method for the DFT-D3 dispersion correction
    2026/07/16 by Victoria Valeeva, Cheuk Hin Ho, Mario Geiger +4
    #physics.comp-ph