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Found 4 papers, 3 papers with code
Look Twice: A Generalist Computational Model Predicts Return Fixations across Tasks and Species
Primates constantly explore their surroundings via saccadic eye movements that bring different parts of an image into high resolution.
Fooling the primate brain with minimal, targeted image manipulation
Here we propose an array of methods for creating minimal, targeted image perturbations that lead to changes in both neuronal activity and perception as reflected in behavior.
Gradient-free activation maximization for identifying effective stimuli
To circumvent this problem, we developed a method for gradient-free activation maximization by combining a generative neural network with a genetic algorithm.
Biologically-plausible learning algorithms can scale to large datasets
These results complement the study by Bartunov et al. (2018), and establish a new benchmark for future biologically plausible learning algorithms on more difficult datasets and more complex architectures.
