77 citations · 87 across the 9 of their papers we have counts for
3 papers · 1 filter
Using Ornstein-Uhlenbeck Process to understand Denoising Diffusion Probabilistic Model and its Noise Schedules
Javier E. Santos, Yen Ting Lin
The aim of this short note is to show that Denoising Diffusion Probabilistic Model DDPM, a non-homogeneous discrete-time Markov process, can be represented by a time-homogeneous co…
A phase transition for finding needles in nonlinear haystacks with LASSO artificial neural networks
Xiaoyu Ma, Sylvain Sardy, Nick Hengartner +2
To fit sparse linear associations, a LASSO sparsity inducing penalty with a single hyperparameter provably allows to recover the important features (needles) with high probability…
What needles do sparse neural networks find in nonlinear haystacks
Sylvain Sardy, Nicolas W Hengartner, Nikolai Bonenko +1
Using a sparsity inducing penalty in artificial neural networks (ANNs) avoids over-fitting, especially in situations where noise is high and the training set is small in comparison…