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1911.05020
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Generative adversarial networks (GAN) based efficient sampling of chemical space for inverse design of inorganic materials
12 November 2019
Yabo Dan
Yong Zhao
Xiang Li
Shaobo Li
Ming Hu
Jianjun Hu
AI4CE
GAN
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Papers citing
"Generative adversarial networks (GAN) based efficient sampling of chemical space for inverse design of inorganic materials"
7 / 7 papers shown
Title
Enhancing Vision-Language Compositional Understanding with Multimodal Synthetic Data
Haoxin Li
Boyang Li
CoGe
65
0
0
03 Mar 2025
End-to-End Crystal Structure Prediction from Powder X-Ray Diffraction
Qingsi Lai
Lin Yao
Zhifeng Gao
Siyuan Liu
Hongshuai Wang
...
Di He
Liwei Wang
Cheng Wang
Guolin Ke
Guolin Ke
15
7
0
08 Jan 2024
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
Artificial Intelligence in Material Engineering: A review on applications of AI in Material Engineering
Lipichanda Goswami
Manoj Deka
Mohendra Roy
AI4CE
17
18
0
15 Sep 2022
Physics Guided Deep Learning for Generative Design of Crystal Materials with Symmetry Constraints
Yong Zhao
Edirisuriya M Dilanga Siriwardane
Zhenyao Wu
Nihang Fu
Mohammed Al-Fahdi
Ming Hu
Jianjun Hu
AI4CE
15
67
0
27 Mar 2022
Deep Learning-Based Inverse Design for Engineering Systems: Multidisciplinary Design Optimization of Automotive Brakes
Seongsin Kim
Min-seok Jwa
Soon-Sik Lee
Sung-Moon Park
Namwoo Kang
AI4CE
11
11
0
27 Feb 2022
Conditional molecular design with deep generative models
Seokho Kang
Kyunghyun Cho
BDL
138
182
0
30 Apr 2018
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