49 citations · 179 across the 33 of their papers we have counts for
38 papers
Bilinear Compressive Security with Finitely Many Samples
Axel Flinth, Semira Einsele, Matilda Kylberg +2
Bilinear Compressive Security (BCS) is a lightweight encryption scheme that combines compressed sensing with a fresh random convolution filter to improve resistance against key-rec…
Boosting Data Augmentation with Stochastic Weight Averaging
Longde Huang, Axel Flinth, Jan E. Gerken
The symmetries of a learning task have become an important factor in designing modern deep learning solutions. Data augmentation is a straightforward and effective way of incorpora…
A sufficient condition for the existence of solutions of singular linear-quadratic vector equations
Rishikesh Yadav, Axel Flinth
We study the existence of solutions for systems of linear-quadratic vector equations with singular linear parts. We derive a sufficient condition for small right hand sides.
Equivariance and Augmentation for Bayesian Neural Networks
Miaowen Dong, Axel Flinth, Jan E. Gerken
Symmetries are important for many deep learning tasks, ranging from applications in the sciences to medical imaging. However, there is an ongoing debate about whether to impose sym…
Conservation Laws from Data Symmetry in Neural Networks
Jakob Galley, Vahid Shahverdi, Axel Flinth
We explore whether intrinsic symmetries of the training data lead to conserved quantities during gradient-flow training of neural networks. Under the assumption that the loss funct…
On the identifiability and semi-algebraicity of ReLU neuromanifolds
Axel Flinth, Stefano Mereta, Michele Pernice
We study several aspects of the semi-algebraicity of the neuromanifold of a feedforward ReLU neural network. We prove that in…