Search Results for author:
Found 7 papers, 1 papers with code
An Out-of-Domain Synapse Detection Challenge for Microwasp Brain Connectomes
The size of image stacks in connectomics studies now reaches the terabyte and often petabyte scales with a great diversity of appearance across brain regions and samples.
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution
Neuroscience has long been an essential driver of progress in artificial intelligence (AI).
A Similarity-preserving Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit
Unfortunately, it is difficult to map their model onto a biologically plausible neural network (NN) with local learning rules.
A Neural Network for Semi-Supervised Learning on Manifolds
Here, we propose a feed-forward neural network capable of semi-supervised learning on manifolds without using an explicit graph representation.
Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks
Many neurons in the brain, such as place cells in the rodent hippocampus, have localized receptive fields, i. e., they respond to a small neighborhood of stimulus space.
OnACID: Online Analysis of Calcium Imaging Data in Real Time
Optical imaging methods using calcium indicators are critical for monitoring the activity of large neuronal populations in vivo.
Clustering is semidefinitely not that hard: Nonnegative SDP for manifold disentangling
In solving hard computational problems, semidefinite program (SDP) relaxations often play an important role because they come with a guarantee of optimality.
