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Materials Learning Algorithms
MALA (Materials Learning Algorithms) is a data-driven framework to accelerate electronic structure calculations based on machine learning. Its purpose is to construct neural-network surrogate models for bypassing computationally expensive steps in state-of-the-art density functional simulations.
- Density functional theory
- electronic structure
- machine-learning
- + 2
- Python
- Fortran
- Shell
- + 1
28
230
BlenderProc
A procedural Blender pipeline for photorealistic training image generation
- Blender
- Dataset creation
- Indoor Scene
- + 4
- Python
- TeX
8
119
Arbor
Arbor is a high-performance library for computational neuroscience simulations with multi-compartment, morphologically-detailed cells, from single cell models to very large networks. Arbor is written from the ground up to help neuroscientists effectively use contemporary and future HPC systems.
- GPU
- High performance computing
- Neural network
- + 4
- C++
- AGS Script
- Python
- + 7
11
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