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Found 4 papers, 1 papers with code
Reproducibility via neural fields of visual illusions induced by localized stimuli
The aim is to understand and model the visual phenomena observed in these experiments, emphasising their nonlinear nature.
Cortical origins of MacKay-type visual illusions: A case for the non-linearity
To study the interaction between retinal stimulation by redundant geometrical patterns and the cortical response in the primary visual cortex (V1), we focus on the MacKay effect (Nature, 1957) and Billock and Tsou's experiments (PNAS, 2007).
Reproducing sensory induced hallucinations via neural fields
In this work, we focus on pattern formation in the visual cortex when the cortical activity is driven by a geometric visual hallucination-like stimulus.
A Geometric Approach of Gradient Descent Algorithms in Linear Neural Networks
We translate a well-known empirical observation of linear neural nets into a conjecture that we call the \emph{overfitting conjecture} which states that, for almost all training data and initial conditions, the trajectory of the corresponding gradient descent system converges to a global minimum.
