25 citations · 40 across the 8 of their papers we have counts for
3 papers · 1 filter
Improving Reproducible Deep Learning Workflows with DeepDIVA
Michele Alberti, Vinaychandran Pondenkandath, Lars Vögtlin +3
The field of deep learning is experiencing a trend towards producing reproducible research. Nevertheless, it is still often a frustrating experience to reproduce scientific results…
Leveraging Random Label Memorization for Unsupervised Pre-Training
Vinaychandran Pondenkandath, Michele Alberti, Sammer Puran +2
We present a novel approach to leverage large unlabeled datasets by pre-training state-of-the-art deep neural networks on randomly-labeled datasets. Specifically, we train the neur…
Are You Tampering With My Data?
Michele Alberti, Vinaychandran Pondenkandath, Marcel Würsch +4
We propose a novel approach towards adversarial attacks on neural networks (NN), focusing on tampering the data used for training instead of generating attacks on trained models. O…