Search Results for author:
Found 7 papers, 3 papers with code
An Explainable and Conformal AI Model to Detect Temporomandibular Joint Involvement in Children Suffering from Juvenile Idiopathic Arthritis
The results show promise for an AI model in the assessment of TMJ involvement in children and as a decision support tool.
A probabilistic estimation of remaining useful life from censored time-to-event data
Our work encourages the inclusion of censored data in predictive maintenance models and highlights the unique advantages that survival analysis offers when it comes to probabilistic RUL estimation and early fault detection.
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.
