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atomistic-machine-learning/schnetpack-gschnet

0
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64 stars·11 forks·Python·MIT·6 views

Schnetpack Gschnet

G-SchNet is a generative neural network that samples molecules by sequentially placing atoms in 3d space. It can be trained on data sets of 3d molecules with variable sizes and compositions. The conditional version, cG-SchNet, explicitly takes chemical and structural properties into account to…

Features

  • Generative Models - Generative extension for 3D molecular structure modeling.

Star history

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Open-source alternatives to Schnetpack Gschnet

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Frequently asked questions

What does atomistic-machine-learning/schnetpack-gschnet do?

G-SchNet is a generative neural network that samples molecules by sequentially placing atoms in 3d space. It can be trained on data sets of 3d molecules with variable sizes and compositions. The conditional version, cG-SchNet, explicitly takes chemical and structural properties into account to…

What are the main features of atomistic-machine-learning/schnetpack-gschnet?

The main features of atomistic-machine-learning/schnetpack-gschnet are: Generative Models.

What are some open-source alternatives to atomistic-machine-learning/schnetpack-gschnet?

Open-source alternatives to atomistic-machine-learning/schnetpack-gschnet include: abisee/pointer-generator — Code for the ACL 2017 paper "Get To The Point: Summarization with Pointer-Generator Networks". addtt/ladder-vae-pytorch. aidc-ai/omni-view — Shanshan Zhao♯ , Qing-Guo Chen , Xuerui Qiu , Jialun Liu , Zhao Xu , Weihua Luo , Kaifu Zhang , Yanye Lu♯. aiff22/dped — Software and pre-trained models for automatic photo quality enhancement using Deep Convolutional Networks. ajbrock/biggan-pytorch — The author's officially unofficial PyTorch BigGAN implementation. aaronjackson/vrn — vrn is a 3D face reconstruction tool that generates three-dimensional volumetric representations of human faces from…