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04/21/2021
Programmable 3D snapshot microscopy with Fourier convolutional networks
3D snapshot microscopy enables volumetric imaging as fast as a camera al...
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01/07/2021
Learning Guided Electron Microscopy with Active Acquisition
Single-beam scanning electron microscopes (SEM) are widely used to acqui...
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06/27/2019
Teaching deep neural networks to localize sources in super-resolution microscopy by combining simulation-based learning and unsupervised learning
Single-molecule localization microscopy constructs super-resolution imag...
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06/12/2018
A Connectome Based Hexagonal Lattice Convolutional Network Model of the Drosophila Visual System
What can we learn from a connectome? We constructed a simplified model o...
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05/28/2018
Discrete flow posteriors for variational inference in discrete dynamical systems
Each training step for a variational autoencoder (VAE) requires us to sa...
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11/06/2017
Extracting low-dimensional dynamics from multiple large-scale neural population recordings by learning to predict correlations
A powerful approach for understanding neural population dynamics is to e...
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11/06/2017
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders
Calcium imaging permits optical measurement of neural activity. Since in...
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09/09/2017
A Deep Structured Learning Approach Towards Automating Connectome Reconstruction from 3D Electron Micrographs
We present a deep structured learning method for neuron segmentation fro...
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07/27/2017
Anisotropic EM Segmentation by 3D Affinity Learning and Agglomeration
The field of connectomics has recently produced neuron wiring diagrams f...
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11/28/2009