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Matthias Kuemmerer

3 accepted papers

2025

What Moves the Eyes: Doubling Mechanistic Model Performance Using Deep Networks to Discover and Test Cognitive Hypotheses

NeurIPS 2025poster

Understanding how humans move their eyes to gather visual information is a central question in neuroscience, cognitive science, and vision research. While recent deep learning (DL) models achieve state-of-the-art performance in predicting human scanpaths, their underlying decision processes remain o…

Cited by 0SourcecodeScholar
2024

Object segmentation from common fate: Motion energy processing enables human-like zero-shot generalization to random dot stimuli

NeurIPS 2024poster

Humans excel at detecting and segmenting moving objects according to the {\it Gestalt} principle of “common fate”. Remarkably, previous works have shown that human perception generalizes this principle in a zero-shot fashion to unseen textures or random dots. In this work, we seek to better understa…

2023

RDumb: A simple approach that questions our progress in continual test-time adaptation

NeurIPS 2023poster

Test-Time Adaptation (TTA) allows to update pre-trained models to changing data distributions at deployment time. While early work tested these algorithms for individual fixed distribution shifts, recent work proposed and applied methods for continual adaptation over long timescales. To examine the…