Search Results for author: Mark Fuge

Found 8 papers, 4 papers with code

IH-GAN: A Conditional Generative Model for Implicit Surface-Based Inverse Design of Cellular Structures

1 code implementation3 Mar 2021 Jun Wang, Wei Wayne Chen, Daicong Da, Mark Fuge, Rahul Rai

Results show that our method can 1) generate various unit cells that satisfy given material properties with high accuracy ($R^2$-scores between target properties and properties of generated unit cells $>98\%$) and 2) improve the optimized structural performance over the conventional variable-density single-type structure.

Airfoil Design Parameterization and Optimization using Bézier Generative Adversarial Networks

1 code implementation21 Jun 2020 Wei Chen, Kevin Chiu, Mark Fuge

The resulted new parameterization can accelerate design optimization convergence by improving the representation compactness while maintaining sufficient representation capacity.

Forming Diverse Teams from Sequentially Arriving People

no code implementations25 Feb 2020 Faez Ahmed, John Dickerson, Mark Fuge

Our method has applications in collaborative work ranging from team formation, the assignment of workers to teams in crowdsourcing, and reviewer allocation to journal papers arriving sequentially.

An Algorithm for Multi-Attribute Diverse Matching

no code implementations7 Sep 2019 Saba Ahmadi, Faez Ahmed, John P. Dickerson, Mark Fuge, Samir Khuller

Bipartite b-matching, where agents on one side of a market are matched to one or more agents or items on the other, is a classical model that is used in myriad application areas such as healthcare, advertising, education, and general resource allocation.

BézierGAN: Automatic Generation of Smooth Curves from Interpretable Low-Dimensional Parameters

no code implementations27 Aug 2018 Wei Chen, Mark Fuge

Many real-world objects are designed by smooth curves, especially in the domain of aerospace and ship, where aerodynamic shapes (e. g., airfoils) and hydrodynamic shapes (e. g., hulls) are designed.

Active Expansion Sampling for Learning Feasible Domains in an Unbounded Input Space

1 code implementation25 Aug 2017 Wei Chen, Mark Fuge

We evaluate AES on three test examples and compare AES with two adaptive sampling methods -- the Neighborhood-Voronoi algorithm and the straddle heuristic -- that operate over fixed input variable bounds.

Active Learning

Diverse Weighted Bipartite b-Matching

1 code implementation23 Feb 2017 Faez Ahmed, John P. Dickerson, Mark Fuge

Bipartite matching, where agents on one side of a market are matched to agents or items on the other, is a classical problem in computer science and economics, with widespread application in healthcare, education, advertising, and general resource allocation.


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