Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling

4 August 2023

Papers citing "Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling"

5 / 5 papers shown

Title
Scalable Diffusion for Materials Generation Mengjiao Yang KwangHwan Cho Amil Merchant Pieter Abbeel Dale Schuurmans Igor Mordatch E. D. Cubuk 19 38 0 18 Oct 2023
Star-Shaped Denoising Diffusion Probabilistic Models Andrey Okhotin Dmitry Molchanov V. Arkhipkin Grigory Bartosh Viktor Ohanesian Aibek Alanov Dmitry Vetrov DiffM 19 12 0 10 Feb 2023
Crystal Diffusion Variational Autoencoder for Periodic Material Generation Tian Xie Xiang Fu O. Ganea Regina Barzilay Tommi Jaakkola DiffM BDL 191 158 0 12 Oct 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 161 1,095 0 27 Apr 2021
Conditional molecular design with deep generative models Seokho Kang Kyunghyun Cho BDL 138 182 0 30 Apr 2018