research
∙
11/20/2022
Overfreezing Meets Overparameterization: A Double Descent Perspective on Transfer Learning of Deep Neural Networks
We study the generalization behavior of transfer learning of deep neural...
share
research
∙
10/21/2022
Boomerang: Local sampling on image manifolds using diffusion models
Diffusion models can be viewed as mapping points in a high-dimensional l...
research
∙
10/11/2021
NFT-K: Non-Fungible Tangent Kernels
Deep neural networks have become essential for numerous applications due...
research
∙
10/08/2021
Evaluating generative networks using Gaussian mixtures of image features
We develop a measure for evaluating the performance of generative networ...
research
∙
06/07/2021
Double Descent and Other Interpolation Phenomena in GANs
We study overparameterization in generative adversarial networks (GANs) ...
research
∙
10/27/2020
Wearing a MASK: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels
High dimensionality poses many challenges to the use of data, from visua...
research
∙
06/25/2020
Ensembles of Generative Adversarial Networks for Disconnected Data
Most current computer vision datasets are composed of disconnected sets,...
research
∙
02/25/2020