Publications

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

Career

Award

BibTeX

Robust Machine Learning Article Interaction Asymmetry: A General Principle for Learning Composable Abstractions Brady, J., von Kügelgen, J., Lachapelle, S., Buchholz, S., Kipf, T., Brendel, W. November 2024, Submitted (Submitted) BibTeX

Robust Machine Learning Conference Paper Rule Extrapolation in Language Models: A Study of Compositional Generalization on OOD Prompts Mészáros, A., Ujváry, S., Brendel, W., Reizinger, P., Huszár, F. In September 2024 (Published) ArXiv BibTeX

Empirical Inference Robust Machine Learning Conference Paper Position: Understanding LLMs Requires More Than Statistical Generalization Reizinger, P., Ujváry, S., Mészáros, A., Kerekes, A., Brendel, W., Huszár, F. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:42365-42390, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) arXiv URL BibTeX

Robust Machine Learning Conference Paper An interventional perspective on identifiability in gaussian lti systems with independent component analysis Rajendran, G., Reizinger, P., Brendel, W., Ravikumar, P. K. :41-70, Causal Learning and Reasoning, March 2024 (Published) PMLR BibTeX

Robust Machine Learning Conference Paper Does CLIP’s Generalization Performance Mainly Stem from High Train-Test Similarity? Mayilvahanan, P., Wiedemer, T., Rusak, E., Bethge, M., Brendel, W. In June 2024 (Published) ArXiv BibTeX

Robust Machine Learning Conference Paper Don’t trust your eyes: on the (un) reliability of feature visualizations Geirhos, R., Zimmermann, R. S., Bilodeau, B., Brendel, W., Kim, B. In June 2024 (Published) ArXiv BibTeX

Robust Machine Learning Conference Paper Effective pruning of web-scale datasets based on complexity of concept clusters Abbas, A., Rusak, E., Tirumala, K., Brendel, W., Chaudhuri, K., Morcos, A. S. In January 2024 (Published) ArXiv BibTeX

Robust Machine Learning Conference Paper InfoNCE: Identifying the Gap Between Theory and Practice Rusak, E., Reizinger, P., Juhos, A., Bringmann, O., Zimmermann, R. S., Brendel, W. In July 2024 (Published) BibTeX

Robust Machine Learning Conference Paper Measuring Per-Unit Interpretability at Scale Without Humans Klindt, D., Zimmermann, R., Brendel, W. In September 2024 (Published) OpenReview BibTeX

Robust Machine Learning Article Translational symmetry in convolutions with localized kernels causes an implicit bias toward high frequency adversarial examples Caro, J. O., Ju, Y., Pyle, R., Dey, S., Brendel, W., Anselmi, F., Patel, A. B. Frontiers in Computational Neuroscience, 18:1387077, June 2024 (Published) Frontiers in Computational Neuroscience BibTeX

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