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Found 8 papers, 3 papers with code
Latent Neural Cellular Automata for Resource-Efficient Image Restoration
Neural cellular automata represent an evolution of the traditional cellular automata model, enhanced by the integration of a deep learning-based transition function.
Harnessing the Computing Continuum across Personalized Healthcare, Maintenance and Inspection, and Farming 4.0
The AI-SPRINT project, launched in 2021 and funded by the European Commission, focuses on the development and implementation of AI applications across the computing continuum.
Scaling Survival Analysis in Healthcare with Federated Survival Forests: A Comparative Study on Heart Failure and Breast Cancer Genomics
Our results underscore the potential of FedSurF++ to improve the scalability and effectiveness of survival analysis in distributed settings while preserving user privacy.
Discriminative Adversarial Privacy: Balancing Accuracy and Membership Privacy in Neural Networks
The remarkable proliferation of deep learning across various industries has underscored the importance of data privacy and security in AI pipelines.
Federated Survival Forests
In this work, we present a novel federated algorithm for survival analysis based on one of the most successful survival models, the random survival forest.
Heterogeneous Datasets for Federated Survival Analysis Simulation
However, the data needed to train survival models are often distributed, incomplete, censored, and confidential.
SGDE: Secure Generative Data Exchange for Cross-Silo Federated Learning
In this context, federated learning is one of the most influential frameworks for privacy-preserving distributed machine learning, achieving astounding results in many natural language processing and computer vision tasks.
Neural Weighted A*: Learning Graph Costs and Heuristics with Differentiable Anytime A*
Recently, the trend of incorporating differentiable algorithms into deep learning architectures arose in machine learning research, as the fusion of neural layers and algorithmic layers has been beneficial for handling combinatorial data, such as shortest paths on graphs.
