Papers Design Synthesis
“Design Synthesis” 태그가 달린 논문 22편 · 필터 해제
Symbolic Reduction for Formal Synthesis of Global Lyapunov Functions
We investigate the formal synthesis of global polynomial Lyapunov functions for polynomial vector fields. We establish that a sign-definite polynomial must satisfy specific algebraic constraints, which we leverage to dev…
Design SynthesisvalidParametric-ControlNet: Multimodal Control in Foundation Models for Precise Engineering Design Synthesis
This paper introduces a generative model designed for multimodal control over text-to-image foundation generative AI models such as Stable Diffusion, specifically tailored for engineering design synthesis. Our model prop…
Design SynthesisMaskPLAN: Masked Generative Layout Planning from Partial Input
Layout planning spanning from architecture to interior design is a slow iterative exploration of ill-defined problems adopting a "I'll know it when I see it" approach to potential solutions. Recent advances in genera…
AttributeDesign SynthesisLayout GenerationModeling Dislocation Dynamics Data Using Semantic Web Technologies
Research in the field of Materials Science and Engineering focuses on the design, synthesis, properties, and performance of materials. An important class of materials that is widely investigated are crystalline materials…
Design SynthesisPhysics-guided training of GAN to improve accuracy in airfoil design synthesis
Generative adversarial networks (GAN) have recently been used for a design synthesis of mechanical shapes. A GAN sometimes outputs physically unreasonable shapes. For example, when a GAN model is trained to output airfoi…
Design SynthesisMulti-modal Machine Learning in Engineering Design: A Review and Future Directions
In the rapidly advancing field of multi-modal machine learning (MMML), the convergence of multiple data modalities has the potential to reshape various applications. This paper presents a comprehensive overview of the cu…
Cross-Modal Information RetrievalDesign SynthesisInformation RetrievalRetrievalUnsupervised Learning of Sampling Distributions for Particle Filters
Accurate estimation of the states of a nonlinear dynamical system is crucial for their design, synthesis, and analysis. Particle filters are estimators constructed by simulating trajectories from a sampling distribution …
Design SynthesisLEAPER: Fast and Accurate FPGA-based System Performance Prediction via Transfer Learning
Machine learning has recently gained traction as a way to overcome the slow accelerator generation and implementation process on an FPGA. It can be used to build performance and resource usage models that enable fast ear…
Design SynthesisTransfer LearningDiffusion Models Beat GANs on Topology Optimization
Structural topology optimization, which aims to find the optimal physical structure that maximizes mechanical performance, is vital in engineering design applications in aerospace, mechanical, and civil engineering. Gene…
Design SynthesisTowards Goal, Feasibility, and Diversity-Oriented Deep Generative Models in Design
Deep Generative Machine Learning Models (DGMs) have been growing in popularity across the design community thanks to their ability to learn and mimic complex data distributions. DGMs are conventionally trained to minimiz…
Design SynthesisDiversityCAD Based Design Optimization of Four-bar Mechanisms: a coronaventilator case study
Design optimization of mechanisms is a promising research area as it results in more energy-efficient machines without compromising performance. However, machine builders do not actually use the design methods described …
Design SynthesisDeep Generative Models in Engineering Design: A Review
Automated design synthesis has the potential to revolutionize the modern engineering design process and improve access to highly optimized and customized products across countless industries. Successfully adapting genera…
Deep Reinforcement LearningDesign SynthesisConditional Cross-Design Synthesis Estimators for Generalizability in Medicaid
While much of the causal inference literature has focused on addressing internal validity biases, both internal and external validity are necessary for unbiased estimates in a target population of interest. However, few …
Causal InferenceDesign SynthesisFunctional Nanomaterials Design in the Workflow of Building Machine-Learning Models
Machine-learning (ML) techniques have revolutionized a host of research fields of chemical and materials science with accelerated, high-efficiency discoveries in design, synthesis, manufacturing, characterization and app…
BIG-bench Machine LearningDesign SynthesisPcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design
Engineering design tasks often require synthesizing new designs that meet desired performance requirements. The conventional design process, which requires iterative optimization and performance evaluation, is slow and d…
Design SynthesisDiversityGenerative Adversarial NetworkPoint ProcessesCreativeGAN: Editing Generative Adversarial Networks for Creative Design Synthesis
Modern machine learning techniques, such as deep neural networks, are transforming many disciplines ranging from image recognition to language understanding, by uncovering patterns in big data and making accurate predict…
Design SynthesisNovelty DetectionRange-GAN: Range-Constrained Generative Adversarial Network for Conditioned Design Synthesis
Typical engineering design tasks require the effort to modify designs iteratively until they meet certain constraints, i.e., performance or attribute requirements. Past work has proposed ways to solve the inverse design …
3D Shape GenerationAttributeDesign SynthesisGenerative Adversarial NetworkBIKED: A Dataset for Computational Bicycle Design with Machine Learning Benchmarks
In this paper, we present "BIKED," a dataset comprised of 4500 individually designed bicycle models sourced from hundreds of designers. We expect BIKED to enable a variety of data-driven design applications for bicycles …
BIG-bench Machine LearningDesign SynthesisDimensionality ReductionGeneral Classification+1Predictive Synthesis of Quantum Materials by Probabilistic Reinforcement Learning
Predictive materials synthesis is the primary bottleneck in realizing new functional and quantum materials. Strategies for synthesis of promising materials are currently identified by time-consuming trial and error appro…
Design Synthesisreinforcement-learningReinforcement LearningReinforcement Learning (RL)MO-PaDGAN: Generating Diverse Designs with Multivariate Performance Enhancement
Deep generative models have proven useful for automatic design synthesis and design space exploration. However, they face three challenges when applied to engineering design: 1) generated designs lack diversity, 2) it is…
Design SynthesisDiversityPoint Processes