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The control problems of complex physical systems have broad applications in science and engineering. Previous studies have shown that generative control methods based on diffusion models offer significant advantages for solving these…

Systems and Control · Electrical Eng. & Systems 2025-02-25 Long Wei , Haodong Feng , Yuchen Yang , Ruiqi Feng , Peiyan Hu , Xiang Zheng , Tao Zhang , Dixia Fan , Tailin Wu

Bio-inspired composites are a great promise for mimicking the extraordinary and highly efficient properties of natural materials. Recent developments in voxel-by-voxel 3D printing have enabled extreme levels of control over the material…

Diffusion models have shown remarkable results in generating 2D images and small-scale 3D objects. However, their application to the synthesis of large-scale 3D scenes has been rarely explored. This is mainly due to the inherent complexity…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Yuheng Liu , Xinke Li , Xueting Li , Lu Qi , Chongshou Li , Ming-Hsuan Yang

Interior design is a complex and creative discipline involving aesthetics, functionality, ergonomics, and materials science. Effective solutions must meet diverse requirements, typically producing multiple deliverables such as renderings…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Yuxuan Yang , Tao Geng

We present a probabilistic model for point cloud generation, which is fundamental for various 3D vision tasks such as shape completion, upsampling, synthesis and data augmentation. Inspired by the diffusion process in non-equilibrium…

Computer Vision and Pattern Recognition · Computer Science 2021-06-15 Shitong Luo , Wei Hu

Human body restoration plays a vital role in various applications related to the human body. Despite recent advances in general image restoration using generative models, their performance in human body restoration remains mediocre, often…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Yiming Zhang , Zhe Wang , Xinjie Li , Yunchen Yuan , Chengsong Zhang , Xiao Sun , Zhihang Zhong , Jian Wang

Diffusion models have made remarkable progress in solving various inverse problems, attributing to the generative modeling capability of the data manifold. Posterior sampling from the conditional score function enable the precious data…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Jinghao Zhang , Zizheng Yang , Qi Zhu , Feng Zhao

The development of new materials typically involves a process of trial and error, guided by insights from past experimental and theoretical findings. The inverse design approach for soft-matter systems has the potential to optimize specific…

Generating diverse and realistic human motion that can physically interact with an environment remains a challenging research area in character animation. Meanwhile, diffusion-based methods, as proposed by the robotics community, have…

Graphics · Computer Science 2024-12-06 Takara E. Truong , Michael Piseno , Zhaoming Xie , C. Karen Liu

Within periodic materials and structures, wave scattering and dispersion occur across constituent material interfaces leading to a banded frequency response. In an earlier paper, the elastodynamics of one-dimensional periodic materials and…

Materials Science · Physics 2023-12-19 M. I. Hussein , G. M. Hulbert , R. A. Scott

The central security issue of outsourced 3D printing (aka AM: Additive Manufacturing), an industry that is expected to dominate manufacturing, is the protection of the digital design (containing the designers' model, which is their…

Cryptography and Security · Computer Science 2025-09-24 Aleksandr Dolgavin , Jacob Gatlin , Moti Yung , Mark Yampolskiy

Diffusion models have recently emerged as powerful generative priors for solving inverse problems. However, training diffusion models in the pixel space are both data-intensive and computationally demanding, which restricts their…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Bowen Song , Soo Min Kwon , Zecheng Zhang , Xinyu Hu , Qing Qu , Liyue Shen

Material responses to static and dynamic stimuli, represented as nonlinear curves, are design targets for engineering functionalities like structural support, impact protection, and acoustic and photonic bandgaps. Three-dimensional…

In 3D printing, stiff fibers (e.g., carbon fiber) can reinforce thermoplastic polymers with limited stiffness. However, existing commercial digital manufacturing software only provides a few simple fiber layout algorithms, which solely use…

Computational Engineering, Finance, and Science · Computer Science 2023-10-31 Xingyuan Sun , Geoffrey Roeder , Tianju Xue , Ryan P. Adams , Szymon Rusinkiewicz

This study investigates human-computer interface generation based on diffusion models to overcome the limitations of traditional template-based design and fixed rule-driven methods. It first analyzes the key challenges of interface…

Human-Computer Interaction · Computer Science 2026-01-13 Rui Liu , Liuqingqing Yang , Runsheng Zhang , Shixiao Wang

Time-fractional differential equations offer a robust framework for capturing intricate phenomena characterized by memory effects, particularly in fields like biotransport and rheology. However, solving inverse problems involving fractional…

Neural and Evolutionary Computing · Computer Science 2024-07-16 Sukirt Thakur , Harsa Mitra , Arezoo M. Ardekani

This paper aims to recover object materials from posed images captured under an unknown static lighting condition. Recent methods solve this task by optimizing material parameters through differentiable physically based rendering. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Xi Chen , Sida Peng , Dongchen Yang , Yuan Liu , Bowen Pan , Chengfei Lv , Xiaowei Zhou

Suspended drums made of 2D materials hold potential for sensing applications. However, the industrialization of these applications is hindered by significant device-to-device variations presumably caused by non-uniform stress distributions…

Generative modeling has recently undergone remarkable advancements, primarily propelled by the transformative implications of Diffusion Probabilistic Models (DPMs). The impressive capability of these models, however, often entails…

Machine Learning · Computer Science 2023-10-03 Gongfan Fang , Xinyin Ma , Xinchao Wang

3D Computer simulations and experiments are employed to study random packings of compressible spherical grains under external confining stress. Of particular interest is the rigid ball limit, which we describe as a continuous transition in…

Soft Condensed Matter · Physics 2009-10-31 Hernan A. Makse , David L. Johnson , Lawrence M. Schwartz
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