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Found 4 papers, 1 papers with code
Towards a "universal translator" for neural dynamics at single-cell, single-spike resolution
Neuroscience research has made immense progress over the last decade, but our understanding of the brain remains fragmented and piecemeal: the dream of probing an arbitrary brain region and automatically reading out the information encoded in its neural activity remains out of reach.
Targeted Neural Dynamical Modeling
These approaches, however, are limited in their ability to capture the underlying neural dynamics (e. g. linear) and in their ability to relate the learned dynamics back to the observed behaviour (e. g. no time lag).
Building population models for large-scale neural recordings: opportunities and pitfalls
Modern recording technologies now enable simultaneous recording from large numbers of neurons.
not-so-BigGAN: Generating High-Fidelity Images on Small Compute with Wavelet-based Super-Resolution
First, we generate images in low-frequency bands by training a sampler in the wavelet domain.
