1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2026★ 1 cited
Inhibitor Transformers and Gated RNNs for Torus Efficient Fully Homomorphic Encryption
Rickard Brännvall, Tony Zhang, Henrik Forsgren +3
This paper introduces efficient modifications to neural network-based sequence processing approaches, laying new grounds for scalable privacy-preserving machine learning under Full…
cs.CV2024
A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning Conventions
Gustav Grund Pihlgren, Konstantina Nikolaidou, Prakash Chandra Chhipa +4
In recent years, deep perceptual loss has been widely and successfully used to train machine learning models for many computer vision tasks, including image synthesis, segmentation…