Machine Learning

We work on algorithms for finding hidden structure in large data sets, using a combination of probabilistic modeling and deep learning, ranging from social media understanding, text mining, and consumer analytics to visual computing and content generation.

Latest Publications

Neural Render Proxies for Interactive and Differentiable Lighting

Neural Render Proxies for Interactive and Differentiable Lighting

July 1, 2026
Eurographics Symposium on Rendering (EGSR) (2026)

Sergio Sancho (ETH Zurich/DisneyResearch|Studios)
Alexander Rath (DisneyResearch|Studios)
Marco Manzi (DisneyResearch|Studios)
Pascal Chang (ETH Zurich/DisneyResearch|Studios)
Amit H. Bermano (ETH Zurich/DisneyResearch|Studios/Tel Aviv University)
Derek Nowrouzezahrai (McGill University/Mila – Quebec AI Institute/CIFAR AI Chair)
Markus Gross (DisneyResearch|Studios/ETH Zurich)
Marios Papas (DisneyResearch|Studios)

Illumination-Aware Spatial Subdivision for Path Guiding

Illumination-Aware Spatial Subdivision for Path Guiding

July 1, 2026
Eurographics Symposium on Rendering (EGSR) (2026)

Fengshi Zheng (Delft University of Technology)
Christoph Peters (Delft University of Technology)
Sebastian Herholz (Blender Institute)
Marco Manzi (DisneyResearch|Studios)
Elmar Eisemann (Delft University of Technology)

CANRIG: Cross-Attention Neural Face Rigging with Variable Local Control

CANRIG: Cross-Attention Neural Face Rigging with Variable Local Control

April 4, 2026
Eurographics (2026)

Arad Mohammadi (ETH Zurich, DisneyResearch|Studios)
Sebastian Weiss (DisneyResearch|Studios)
Jakob Buhmann (DisneyResearch|Studios)
Loic Ciccone (DisneyResearch|Studios)
Robert Sumner (DisneyResearch|Studios)
Derek Bradley (DisneyResearch|Studios)
Martin Guay (DisneyResearch|Studios)

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