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DEPARTMENTS

Emperical Interference

Haptic Intelligence

Modern Magnetic Systems

Perceiving Systems

Physical Intelligence

Robotic Materials

Social Foundations of Computation

Research Groups

Autonomous Vision

Autonomous Learning

Bioinspired Autonomous Miniature Robots

Dynamic Locomotion

Embodied Vision

Human Aspects of Machine Learning

Intelligent Control Systems

Learning and Dynamical Systems

Locomotion in Biorobotic and Somatic Systems

Micro, Nano, and Molecular Systems

Movement Generation and Control

Neural Capture and Synthesis

Physics for Inference and Optimization

Organizational Leadership and Diversity

Probabilistic Learning Group

Topics

Robot Learning

Conference Paper

2022

Autonomous Learning

Robotics

AI

Career

Award

Statistical Learning Theory Article Advancing research on unconscious priming: When can scientists claim an indirect task advantage? Meyen, S., Zerweck, I., Amado, C., von Luxburg, U., Franz, V. Journal of Experimental Psychology: General, 151(1):65-81, 2022 (Published) DOI BibTeX
Statistical Learning Theory Article Contextual Cueing May Not Be Unconscious Meyen, S. V. L. U. F. V. H. Perception, 50(1_Suppl):51-51, 2021 (Published) BibTeX
Statistical Learning Theory Article Group decisions based on confidence weighted majority voting Meyen, S., Sigg, D. M. B., von Luxburg, U., Franz, V. H. Cognitive Research: Principles and Implications, 6:18, 2021 (Published) DOI URL BibTeX
Statistical Learning Theory Article Estimation of perceptual scales using ordinal embedding Haghiri, S., Wichmann, F. A., von Luxburg, U. Journal of Vision, 20(9), 2020 (Published) DOI URL BibTeX
Statistical Learning Theory Article Two-sample Hypothesis Testing for Inhomogeneous Random Graphs Ghoshdastidar, D., Gutzeit, M., Carpentier, A., von Luxburg, U. Annals of Statistics, 48(4):2208-2229, 2020 BibTeX
Empirical Inference Statistical Learning Theory Article Design and Analysis of the NIPS 2016 Review Process Shah*, N., Tabibian*, B., Muandet, K., Guyon, I., von Luxburg, U. Journal of Machine Learning Research, 19(49):1-34, 2018, *equal contribution (Published) arXiv URL BibTeX
Statistical Learning Theory Article Lens Depth Function and k-Relative Neighborhood Graph: Versatile Tools for Ordinal Data Analysis Kleindessner, M., von Luxburg, U. Journal of Machine Learning Research (JMLR), Journal of Machine Learning Research, 18, 2017 BibTeX