SchNetPack: A Deep Learning Toolbox for Atomistic Systems

Engineering & Materials Science

• Deep learning 82%
• Neural networks 55%
• Molecules 44%
• Potential energy surfaces 38%
• Chemical properties 25%
• Large dataset 24%
• Atoms 23%
• Tensors 22%
• Deep neural networks 22%
• Graphics processing unit 21%

Chemical Compounds

• Quantum Chemical Property 79%
• Potential Energy Surface 43%
• Molecule 31%
• Block Like Crystal 31%
• Simulation 29%
• Environment 26%
• Application 14%

Physics & Astronomy

• learning 100%
• environment simulation 27%
• molecules 19%
• chemical properties 19%
• education 18%
• potential energy 15%
• tensors 13%
• evaluation 11%
• symmetry 10%
• atoms 9%