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Found 3 papers, 1 papers with code
Optimizing the Consumption of Spiking Neural Networks with Activity Regularization
Reducing energy consumption is a critical point for neural network models running on edge devices.
Efficient Blind-Spot Neural Network Architecture for Image Denoising
Standard denoising techniques, which use deep neural networks at their core, require pairs of clean and noisy images for its training.
Learning Generative Models using Denoising Density Estimators
Learning probabilistic models that can estimate the density of a given set of samples, and generate samples from that density, is one of the fundamental challenges in unsupervised machine learning.
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Density Estimation
on UCI MINIBOONE
