Mesh neural cellular automata
Texture modeling and synthesis are essential for enhancing the realism of virtual
environments. Methods that directly synthesize textures in 3D offer distinct advantages to the …
environments. Methods that directly synthesize textures in 3D offer distinct advantages to the …
Comparison and validation of stochastic microstructure characterization and reconstruction: Machine learning vs. deep learning methodologies
In the world of computational materials science, the knowledge of microstructure is vital in
understanding the process-microstructure–property linkage across various length-scales. To …
understanding the process-microstructure–property linkage across various length-scales. To …
A generative model for texture synthesis based on optimal transport between feature distributions
We propose GOTEX, a general framework for texture synthesis by optimization that
constrains the statistical distribution of local features. While our model encompasses several …
constrains the statistical distribution of local features. While our model encompasses several …
In silico formulation optimization and particle engineering of pharmaceutical products using a generative artificial intelligence structure synthesis method
T Hornick, C Mao, A Koynov, P Yawman… - Nature …, 2024 - nature.com
Pharmaceutical drug dosage forms are critical for ensuring the effective and safe delivery of
active pharmaceutical ingredients to patients. However, traditional formulation development …
active pharmaceutical ingredients to patients. However, traditional formulation development …
3D microstructural generation from 2D images of cement paste using generative adversarial networks
Establishing a realistic three-dimensional (3D) microstructure is a crucial step for studying
microstructure development of hardened cement pastes. However, acquiring 3D …
microstructure development of hardened cement pastes. However, acquiring 3D …
Wasserstein generative models for patch-based texture synthesis
This work addresses texture synthesis by relying on the local representation of images
through their patch distributions. The main contribution is a framework that imposes the …
through their patch distributions. The main contribution is a framework that imposes the …
G-Style: Stylized Gaussian Splatting
ÁS Kovács, P Hermosilla, RG Raidou - arXiv preprint arXiv:2408.15695, 2024 - arxiv.org
We introduce G-Style, a novel algorithm designed to transfer the style of an image onto a 3D
scene represented using Gaussian Splatting. Gaussian Splatting is a powerful 3D …
scene represented using Gaussian Splatting. Gaussian Splatting is a powerful 3D …
Stochastic reconstruction and performance prediction of cathode microstructures based on deep learning
X Yang, C He, L Yang, WL Song, HS Chen - Journal of Power Sources, 2024 - Elsevier
The effective properties of lithium-ion battery (LIB) cathode are determined by both the
volume fractions of constituents and the morphological features of microstructure. However …
volume fractions of constituents and the morphological features of microstructure. However …
Implicit Neural Representation of Tileable Material Textures
We explore sinusoidal neural networks to represent periodic tileable textures. Our approach
leverages the Fourier series by initializing the first layer of a sinusoidal neural network with …
leverages the Fourier series by initializing the first layer of a sinusoidal neural network with …
Procedural generation of 3D karst caves with speleothems
K Franke, H Müller - Computers & Graphics, 2022 - Elsevier
A comprehensive method for generating natural looking virtual karst caves is presented. The
method includes the network and the local shape of cave passages, the appearance of the …
method includes the network and the local shape of cave passages, the appearance of the …