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20222025
most citedBridging the Gap: Differentially Private Equivariant Deep Learning for Medical Image Analysis

2 citations · 3 across the 4 of their papers we have counts for

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cs.CV2025

Optimizing Rank for High-Fidelity Implicit Neural Representations

Julian McGinnis, Florian A. Hölzl, Suprosanna Shit +6

Implicit Neural Representations (INRs) based on vanilla Multi-Layer Perceptrons (MLPs) are widely believed to be incapable of representing high-frequency content. This has directed…

cs.CV2023★ 1 cited

Equivariant Differentially Private Deep Learning: Why DP-SGD Needs Sparser Models

Florian A. Hölzl, Daniel Rueckert, Georgios Kaissis

Differentially Private Stochastic Gradient Descent (DP-SGD) limits the amount of private information deep learning models can memorize during training. This is achieved by clipping…