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Found 5 papers, 3 papers with code
Probabilistic Survival Analysis by Approximate Bayesian Inference of Neural Networks
In this paper, we study the benefits of modeling uncertainty in deep neural networks for survival analysis with a focus on prediction and calibration performance.
Predicting Survival Time of Ball Bearings in the Presence of Censoring
In this paper, we propose a novel approach to predict the time to failure in ball bearings using survival analysis.
Computationally Efficient Labeling of Cancer Related Forum Posts by Non-Clinical Text Information Retrieval
We produce a fully-functional prototype that can retrieve, cluster and present information about cancer trajectories from non-clinical forum posts.
Cloud K-SVD for Image Denoising
Cloud K-SVD is a dictionary learning algorithm that can train at multiple nodes and hereby produce a mutual dictionary to represent low-dimensional geometric structures in image data.
Super-convergence and Differential Privacy: Training faster with better privacy guarantees
The combination of deep neural networks and Differential Privacy has been of increasing interest in recent years, as it offers important data protection guarantees to the individuals of the training datasets used.
