A Conditional Generative Model for Predicting Material Microstructures from Processing Methods

4 October 2019

Papers citing "A Conditional Generative Model for Predicting Material Microstructures from Processing Methods"

6 / 6 papers shown

Title
GrainPaint: A multi-scale diffusion-based generative model for microstructure reconstruction of large-scale objects Nathan Hoffman Cashen Diniz Dehao Liu T. Rodgers Anh Tran Mark Fuge AI4CE DiffM 125 1 0 18 Feb 2025
Offline Inverse Constrained Reinforcement Learning for Safe-Critical Decision Making in Healthcare Nan Fang Guiliang Liu Wei Gong OffRL 87 0 0 10 Oct 2024
Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Towards ML-assisted Advanced Manufacturing Scott Howland Lara Kassab K. Kappagantula Henry Kvinge Tegan H. Emerson AI4CE 60 7 0 13 Jan 2023
Artificial intelligence approaches for materials-by-design of energetic materials: state-of-the-art, challenges, and future directions Joseph B. Choi Phong C. H. Nguyen O. Sen H. Udaykumar Stephen Seung-Yeob Baek PINN AI4CE 62 12 0 15 Nov 2022
3DMaterialGAN: Learning 3D Shape Representation from Latent Space for Materials Science Applications Devendra K. Jangid Neal R. Brodnik Amil Khan M. Echlin Tresa M. Pollock Samantha Daly B. S. Manjunath GAN 3DV 29 3 0 27 Jul 2020
Microstructure Generation via Generative Adversarial Network for Heterogeneous, Topologically Complex 3D Materials Tim Hsu W. Epting Hokon Kim H. Abernathy Gregory A. Hackett A. Rollett P. Salvador Elizabeth A. Holm 35 83 0 22 Jun 2020