zoom_in Click to enlarge

Max Welling

▲ ▼

description Max Welling Overview

Max Welling is a Dutch computer scientist specializing in machine learning. He is a research professor at the University of Amsterdam and holds positions at the University of California, Irvine. His research has contributed to variational inference, graph convolutional networks (notably the 2016 Kipf–Welling paper), and probabilistic deep learning. He has served in leadership roles at the European Laboratory for Learning and Information Systems (ELLIS) and has worked with Qualcomm on AI research.

He was elected a fellow of the IEEE for his contributions to the field.

help Max Welling FAQ

What institutions is Max Welling affiliated with?

Max Welling is a Dutch computer scientist who serves as a research professor at the University of Amsterdam. He also holds a faculty position at the University of California, Irvine, splitting his time between Europe and the US.

What are Max Welling's main contributions to machine learning?

Welling has made foundational contributions to machine learning, particularly in the areas of variational inference and graph convolutional networks (GCNs). His pioneering work on GCNs has been instrumental in the rapid development of geometric deep learning.

Did Max Welling work in the tech industry?

Yes, Welling has maintained strong ties to the tech industry, notably serving as a Distinguished Scientist and Vice President at Qualcomm. In this role, he helped bridge the gap between academic AI research and commercial mobile hardware applications.

What is variational inference in Max Welling's research?

Variational inference, a key area of Welling's work, is a machine learning technique used to approximate complex probability distributions. It is a fundamental method used in modern generative AI to make probabilistic models run efficiently on large datasets.