2022/03/16 by Gitta Kutyniok, Kutyniok, Gitta · 2 voices · 6 citations
Computer Science · Engineering · Mathematics · #Advanced Data Processing Techniques #Artificial general intelligence #Artificial intelligence #Artificial neural network #Computational Physics and Python Applications #Computer science #Computer security #Engineering #Focus (optics) #Foundation (evidence) #Key (lock) #Law #Management science #Neural Networks and Applications #Political science #Witness #cs.LG #math.HO #msc:35C20 #msc:41A25 #msc:42C15 #msc:65D18 #msc:68T07 #stat.ML
paper · pdf · doi:10.48550/arxiv.2203.08890
published in arXiv (Cornell University) (Cornell University) · 16 pages, 7 figures
arxiv created 2022/03/16 · openalex publication_date 2022/03/16 · arxiv updated 2022/03/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We currently witness the spectacular success of artificial intelligence in both science and public life. However, the development of a rigorous mathematical foundation is still at an early stage. In this survey article, which is based on an invited lecture at the International Congress of Mathematicians 2022, we will in particular focus on the current "workhorse" of artificial intelligence, namely deep neural networks. We will present the main theoretical directions along with several exemplary results and discuss key open problems.