Marco Seeland

Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks

Dropout is not all you need to prevent gradient leakage

Model-based data generation for the evaluation of functional reliability and resilience of distributed machine learning systems against abnormal cases

Combining Variational Modeling with Partial Gradient Perturbation to Prevent Deep Gradient Leakage

Precode-a generic model extension to prevent deep gradient leakage

Crowd‐sourced plant occurrence data provide a reliable description of macroecological gradients

Trash or treasure? machine-learning based pcb layout anomaly detection with anopcb

The flora incognita app–interactive plant species identification