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Found 6 papers, 0 papers with code
Deep Representation for Connected Health: Semi-supervised Learning for Analysing the Risk of Urinary Tract Infections in People with Dementia
Machine learning techniques combined with in-home monitoring technologies provide a unique opportunity to automate diagnosis and early detection of adverse health conditions in long-term conditions such as dementia.
Continual Learning Using Multi-view Task Conditional Neural Networks
The changes in goals or data are referred to as new tasks in a continual learning model.
Continual Learning Using Bayesian Neural Networks
The catastrophic forgetting is an inevitable problem in continual learning models for dynamic environments.
Continual Learning in Deep Neural Network by Using a Kalman Optimiser
The results show that our approach enables the model to continually learn and adapt to the new changes without forgetting the previously learned tasks.
Kalman Filter Modifier for Neural Networks in Non-stationary Environments
Learning in a non-stationary environment is an inevitable problem when applying machine learning algorithm to real world environment.
Segment Parameter Labelling in MCMC Mean-Shift Change Detection
This work addresses the problem of segmentation in time series data with respect to a statistical parameter of interest in Bayesian models.
