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Found 6 papers, 2 papers with code
Phases of two-dimensional spinless lattice fermions with first-quantized deep neural-network quantum states
First-quantized deep neural network techniques are developed for analyzing strongly coupled fermionic systems on the lattice.
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.
A structured matrix factorization framework for large scale calcium imaging data analysis
We present a structured matrix factorization approach to analyzing calcium imaging recordings of large neuronal ensembles.
Neurons and Cognition Quantitative Methods Applications
Robust learning of low-dimensional dynamics from large neural ensembles
We show on model data that the parameters of latent linear dynamical systems can be recovered, and that even if the dynamics are not stationary we can still recover the true latent subspace.
Sparse nonnegative deconvolution for compressive calcium imaging: algorithms and phase transitions
We propose a compressed sensing (CS) calcium imaging framework for monitoring large neuronal populations, where we image randomized projections of the spatial calcium concentration at each timestep, instead of measuring the concentration at individual locations.
Bayesian spike inference from calcium imaging data
We present efficient Bayesian methods for extracting neuronal spiking information from calcium imaging data.
Neurons and Cognition Quantitative Methods Applications
