logo
ResearchBunny Logo
A generative deep learning framework for inverse design of compositionally complex bulk metallic glasses

Engineering and Technology

A generative deep learning framework for inverse design of compositionally complex bulk metallic glasses

Z. Zhou, Y. Shang, et al.

Discover a groundbreaking generative deep-learning framework for designing complex bulk metallic glasses, developed by Ziqing Zhou, Yinghui Shang, Xiaodi Liu, and Yong Yang. This innovative approach leverages GANs and Boosted Trees for data generation and evaluation, showcasing the potential for novel BMG compositions through systematic data investigation and experimental validation.

00:00
00:00
Playback language: English
Citation Metrics
Citations
0
Influential Citations
0
Reference Count
0

Note: The citation metrics presented here have been sourced from Semantic Scholar and OpenAlex.

Related Publications

Explore these studies to deepen your understanding of the subject.

Design and Analysis of a Deep Learning Ensemble Framework Model for the Detection of COVID-19 and Pneumonia Using Large-Scale CT Scan and X-ray Image Datasets
Medicine and Health

Design and Analysis of a Deep Learning Ensemble Framework Model for the Detection of COVID-19 and Pneumonia Using Large-Scale CT Scan and X-ray Image Datasets

X. Xue, S. Chinnaperumal, et al.

A generative artificial intelligence framework based on a molecular diffusion model for the design of metal-organic frameworks for carbon capture
Chemistry

A generative artificial intelligence framework based on a molecular diffusion model for the design of metal-organic frameworks for carbon capture

H. Park, X. Yan, et al.

A Generalized Explanation Framework for Visualization of Deep Learning Model Predictions
Computer Science

A Generalized Explanation Framework for Visualization of Deep Learning Model Predictions

P. Wang and N. Vasconcelos

A multimodal deep learning approach for the prediction of cognitive decline and its effectiveness in clinical trials for Alzheimer’s disease
Medicine and Health

A multimodal deep learning approach for the prediction of cognitive decline and its effectiveness in clinical trials for Alzheimer’s disease

C. Wang, H. Tachimori, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny