Vitruvion: A Generative Model of Parametric CAD Sketches

Ari SeffBlog

Ari Seff, Wenda Zhou, Nick Richardson, and Ryan P. AdamsInternational Conference on Learning Representations (ICLR) 2022PaperVideoCode & model weights Vitruvion is a transformer-based model trained to generate parametric computer-aided design (CAD) sketches. It shows promise to augment mechanical design via tasks such as converting hand drawings to CAD models, autocompleting sketches, and inferring intended constraints. Overview Parametric CAD tools are the predominant way engineers specify physical structures, from bicycle pedals to airplanes to printed circuit boards. They empower users to explore parameterized variations on their designs, while also providing a structured representation for simulation and manufacturing. At an operational level, parametric CAD starts with the specification of two-dimensional geometric representations, referred to as “sketches”. A sketch consists of a collection … Read More

Using 3D Printing to Develop Rapid-Response PPE Manufacturing

Geoffrey RoederBlog

SARS-CoV-2 cases are beginning to rise again as we head into October. In part due to Labor Day celebrations and the return of many students to in-person classes, the latest National CDC forecasts predict up to 7,400 new COVID-19 deaths per week in our near future. Back during the first spike, one of the major challenges that emerged was a shortage of personal protective equipment and resulting threat to our medical practitioners. Many academic communities paused research pursuits to address this challenge, with my group among them. This post covers our successes, setbacks, and a vision for addressing inevitable future shortages through effective, distributed rapid-response manufacturing. In early April 2020, after daily COVID-19 infections in New York had increased from … Read More

Video: Introduction to Convex Optimization

Ryan AdamsVideo

Convex objective functions are the ones we understand the best. This video explains how things like linear programming can capture real-world optimization problems. This is part of a series of videos for COS 302: Mathematics for Numerical Computation and Machine Learning, replacing lectures after the course went remote due to the COVID-19 pandemic.

Video: Basics of Optimization

Ryan AdamsVideo

Optimization is a huge topic of tremendous importance. In this video we hit some of the high points to give you the big picture. This is part of a series of videos for COS 302: Mathematics for Numerical Computation and Machine Learning, replacing lectures after the course went remote due to the COVID-19 pandemic.

Video: Information Theory Basics

Ryan AdamsVideo

Information theory is a fascinating topic that informs many of the ways we think about structure in data. This video provides a brief overview of some of the concepts, inspired by the lectures of my PhD advisor, the late David MacKay. This is part of a series of videos for COS 302: Mathematics for Numerical Computation and Machine Learning, replacing lectures after the course went remote due to the COVID-19 pandemic.

Video: The Gaussian Distribution

Ryan AdamsVideo

It’s difficult to overstate the centrality of the Gaussian distribution to machine learning, statistics, and many other natural sciences. This video talks about some of the reasons this distribution is special. This is part of a series of videos for COS 302: Mathematics for Numerical Computation and Machine Learning, replacing lectures after the course went remote due to the COVID-19 pandemic.

Video: Useful Inequalities and Limit Theorems

Ryan AdamsVideo

This video talks about Chebyshev, Markov, Jensen, and friends. This is part of a series of videos for COS 302: Mathematics for Numerical Computation and Machine Learning, replacing lectures after the course went remote due to the COVID-19 pandemic.

Video: Dependence and Independence

Ryan AdamsVideo

To do interesting things with joint distributions, they need to have dependence structure. This is part of a series of videos for COS 302: Mathematics for Numerical Computation and Machine Learning, replacing lectures after the course went remote due to the COVID-19 pandemic.

Video: Basics of Joint Probability

Ryan AdamsVideo

From a modeling point of view, joint probability distributions are where the action is. They let you posit latent structure and reason about conditional probability. This video gives an overview of the basics of joint random variables. This is part of a series of videos for COS 302: Mathematics for Numerical Computation and Machine Learning, replacing lectures after the course went remote due to the COVID-19 pandemic.

Video: Some Useful Probability Distributions

Ryan AdamsVideo

There are some distributions that come up over and over again in machine learning and statistics. In this video, I give an overview of some distributions to be aware of. This is part of a series of videos for COS 302: Mathematics for Numerical Computation and Machine Learning, replacing lectures after the course went remote due to the COVID-19 pandemic.