741 citations · 772 across the 11 of their papers we have counts for
6 papers · 1 filter
Inverse design with conditional cascaded diffusion models
Milad Habibi, Mark Fuge
Adjoint-based design optimizations are usually computationally expensive and those costs scale with resolution. To address this, researchers have proposed machine learning approach…
Bayesian Inverse Problems with Conditional Sinkhorn Generative Adversarial Networks in Least Volume Latent Spaces
Qiuyi Chen, Panagiotis Tsilifis, Mark Fuge
Solving inverse problems in scientific and engineering fields has long been intriguing and holds great potential for many applications, yet most techniques still struggle to addres…
Least Volume Analysis
Qiuyi Chen, Cashen Diniz, Mark Fuge
This paper introduces Least Volume (LV)--a simple yet effective regularization method inspired by geometric intuition--that reduces the number of latent dimensions required by an a…
Deep learning for molecular design - a review of the state of the art
Daniel C. Elton, Zois Boukouvalas, Mark D. Fuge +1
In the space of only a few years, deep generative modeling has revolutionized how we think of artificial creativity, yielding autonomous systems which produce original images, musi…
BézierGAN: Automatic Generation of Smooth Curves from Interpretable Low-Dimensional Parameters
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., hull…
Active Expansion Sampling for Learning Feasible Domains in an Unbounded Input Space
Wei Chen, Mark Fuge
Many engineering problems require identifying feasible domains under implicit constraints. One example is finding acceptable car body styling designs based on constraints like aest…