research
∙
05/18/2023
Quantifying the robustness of deep multispectral segmentation models against natural perturbations and data poisoning
In overhead image segmentation tasks, including additional spectral band...
share
research
∙
03/24/2023
How many dimensions are required to find an adversarial example?
Past work exploring adversarial vulnerability have focused on situations...
research
∙
03/10/2023
Fast computation of permutation equivariant layers with the partition algebra
Linear neural network layers that are either equivariant or invariant to...
research
∙
02/28/2023
Robustness of edited neural networks
Successful deployment in uncertain, real-world environments requires tha...
research
∙
02/16/2023
Exploring the Representation Manifolds of Stable Diffusion Through the Lens of Intrinsic Dimension
Prompting has become an important mechanism by which users can more effe...
research
∙
11/19/2022
Neural frames: A Tool for Studying the Tangent Bundles Underlying Image Datasets and How Deep Learning Models Process Them
The assumption that many forms of high-dimensional data, such as images,...
research
∙
10/03/2022
Convolutional networks inherit frequency sensitivity from image statistics
It is widely acknowledged that trained convolutional neural networks (CN...
research
∙
05/27/2022
On the Symmetries of Deep Learning Models and their Internal Representations
Symmetry has been a fundamental tool in the exploration of a broad range...
research
∙
03/15/2022
