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07/11/2023
DDGM: Solving inverse problems by Diffusive Denoising of Gradient-based Minimization
Inverse problems generally require a regularizer or prior for a good sol...
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06/16/2023
Stretched sinograms for limited-angle tomographic reconstruction with neural networks
We present a direct method for limited angle tomographic reconstruction ...
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06/06/2022
Stacked unsupervised learning with a network architecture found by supervised meta-learning
Stacked unsupervised learning (SUL) seems more biologically plausible th...
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04/15/2022
Kernel similarity matching with Hebbian neural networks
Recent works have derived neural networks with online correlation-based ...
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04/15/2022
Sensitivity of sparse codes to image distortions
Sparse coding has been proposed as a theory of visual cortex and as an u...
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09/21/2019
Learning Dense Voxel Embeddings for 3D Neuron Reconstruction
We show dense voxel embeddings learned via deep metric learning can be e...
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02/13/2019
Variance-Preserving Initialization Schemes Improve Deep Network Training: But Which Variance is Preserved?
Before training a neural net, a classic rule of thumb is to randomly ini...
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01/31/2019