(New Orleans, December 03, 2022, Website)

Previous MATH-AI Workshops

Overview

Mathematical reasoning is a core ability of human intelligence and plays an important role in the development of general machine intelligence. The machine learning community has contributed significantly to mathematical reasoning research in the last decades, and recently, there has been a surge of interest in this domain. For example, large neural models have led to rapid progress in areas ranging from word problems to formal theorem proving. However, there is a large performance gap between models and top mathematicians. To this end, the MATH-AI workshop will center around the question:

“How can machines achieve human-level mathematical reasoning?”

Specifically, the goal of this workshop is to find out “when machines can surpass human experts in different mathematical domains?”. To investigate this question, we are interested in bringing together a group of scholars from various backgrounds, institutions, and disciplines to discuss areas related to the following:

The intended outcome is to identify missing elements and meaningful directions for future research related to mathematical reasoning. To this end, we welcome papers on areas related, but not limited, to:

In addition to the problem areas above, we are interested in research related to the following themes:


Speakers & Panelists

Noah D. Goodman
Noah D. Goodman
Stanford University
Cezary Kaliszyk
Cezary Kaliszyk
University of Innsbruck
More Info

Pan Lu
Pan Lu
UCLA, AI2
Sean Welleck
Sean Welleck
UW, AI2
Yuhuai (Tony) Wu
Yuhuai (Tony) Wu
Stanford, Google
Percy Liang
Percy Liang
Stanford

Program Committee


Related Venues


Contact: mathai.neurips2022@gmail.com.