22 citations · 39 across the 4 of their papers we have counts for
4 papers
OmniMouse: Scaling properties of multi-modal, multi-task Brain Models on 150B Neural Tokens
Konstantin F. Willeke, Polina Turishcheva, Alex Gilbert +18
Scaling data and artificial neural networks has transformed AI, driving breakthroughs in language and vision. Whether similar principles apply to modeling brain activity remains un…
The Sensorium competition on predicting large-scale mouse primary visual cortex activity
Konstantin F. Willeke, Paul G. Fahey, Mohammad Bashiri +12
The neural underpinning of the biological visual system is challenging to study experimentally, in particular as the neuronal activity becomes increasingly nonlinear with respect t…
Learning From Brains How to Regularize Machines
Zhe Li, Wieland Brendel, Edgar Y. Walker +7
Despite impressive performance on numerous visual tasks, Convolutional Neural Networks (CNNs) --- unlike brains --- are often highly sensitive to small perturbations of their input…
Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data
E. Kelly Buchanan, Ian Kinsella, Ding Zhou +17
Calcium imaging has revolutionized systems neuroscience, providing the ability to image large neural populations with single-cell resolution. The resulting datasets are quite large…