444 citations · 1.6k across the 80 of their papers we have counts for
4 papers · 1 filter
TT-NF: Tensor Train Neural Fields
Anton Obukhov, Mikhail Usvyatsov, Christos Sakaridis +2
Learning neural fields has been an active topic in deep learning research, focusing, among other issues, on finding more compact and easy-to-fit representations. In this paper, we…
Spectral Tensor Train Parameterization of Deep Learning Layers
Anton Obukhov, Maxim Rakhuba, Alexander Liniger +4
We study low-rank parameterizations of weight matrices with embedded spectral properties in the Deep Learning context. The low-rank property leads to parameter efficiency and permi…
The Hidden Uncertainty in a Neural Networks Activations
Janis Postels, Hermann Blum, Yannick Strümpler +4
The distribution of a neural network's latent representations has been successfully used to detect out-of-distribution (OOD) data. This work investigates whether this distribution…
Dynamic Filter Networks
Bert De Brabandere, Xu Jia, Tinne Tuytelaars +1
In a traditional convolutional layer, the learned filters stay fixed after training. In contrast, we introduce a new framework, the Dynamic Filter Network, where filters are genera…