1.3k citations · 2.8k across the 12 of their papers we have counts for
12 papers
Vitruvion: A Generative Model of Parametric CAD Sketches
Ari Seff, Wenda Zhou, Nick Richardson +1
Parametric computer-aided design (CAD) tools are the predominant way that engineers specify physical structures, from bicycle pedals to airplanes to printed circuit boards. The key…
SketchGraphs: A Large-Scale Dataset for Modeling Relational Geometry in Computer-Aided Design
Ari Seff, Yaniv Ovadia, Wenda Zhou +1
Parametric computer-aided design (CAD) is the dominant paradigm in mechanical engineering for physical design. Distinguished by relational geometry, parametric CAD models begin as…
Discrete Object Generation with Reversible Inductive Construction
Ari Seff, Wenda Zhou, Farhan Damani +2
The success of generative modeling in continuous domains has led to a surge of interest in generating discrete data such as molecules, source code, and graphs. However, constructio…
Continual Learning in Generative Adversarial Nets
Ari Seff, Alex Beatson, Daniel Suo +1
Developments in deep generative models have allowed for tractable learning of high-dimensional data distributions. While the employed learning procedures typically assume that trai…
Learning from Maps: Visual Common Sense for Autonomous Driving
Ari Seff, Jianxiong Xiao
Today's autonomous vehicles rely extensively on high-definition 3D maps to navigate the environment. While this approach works well when these maps are completely up-to-date, safe…
LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop
Fisher Yu, Ari Seff, Yinda Zhang +3
While there has been remarkable progress in the performance of visual recognition algorithms, the state-of-the-art models tend to be exceptionally data-hungry. Large labeled traini…