Capsule Networks have emerged as a powerful class of deep learning
archi...
Predicting emissions for gas turbines is critical for monitoring harmful...
Self-supervised learning algorithms based on instance discrimination
eff...
The recent emergence of Self-Supervised Learning (SSL) as a fundamental
...
Hyperbolic manifolds for visual representation learning allow for effect...
Federated Learning (FL) presents a decentralized approach to model train...
Craters are amongst the most important morphological features in planeta...
Yield forecasting is a critical first step necessary for yield optimisat...
Lifelong domain adaptation remains a challenging task in machine learnin...
Capsule networks were proposed as an alternative approach to Convolution...
We present automatically parameterised Fully Homomorphic Encryption (FHE...
Fully Homomorphic Encryption (FHE) is a relatively recent advancement in...
Bootstrap Your Own Latent (BYOL) introduced an approach to self-supervis...
Data sharing remains a major hindering factor when it comes to adopting
...
Recently, contrastive self-supervised learning has become a key componen...
Multi-step prediction is considered of major significance for time serie...
This paper proposes an enhanced natural language generation system combi...
Precipitation data from rain gauges is fundamental across many lines of
...
Retail food packaging contains information which informs choice and can ...
Effective plant growth and yield prediction is an essential task for
gre...
Deep Learning has attracted considerable attention across multiple
appli...
Capsule Networks are a recently proposed alternative for constructing Ne...
This paper proposes the first step towards a novel unified framework for...