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Found 5 papers, 0 papers with code
Organ localisation using supervised and semi supervised approaches combining reinforcement learning with imitation learning
The results of experiments on localisation of the Spleen, Left and Right Kidneys in CT Images using supervised and semi supervised learning (SSL) demonstrate the ability to address data limitations with a much smaller data set and fewer annotations, compared to other state-of-the-art methods.
Dynamic Silos: Increased Modularity in Intra-organizational Communication Networks during the Covid-19 Pandemic
Workplace communications around the world were drastically altered by Covid-19, related work-from-home orders, and the rise of remote work.
Learning without gradient descent encoded by the dynamics of a neurobiological model
The success of state-of-the-art machine learning is essentially all based on different variations of gradient descent algorithms that minimize some version of a cost or loss function.
Inducing a hierarchy for multi-class classification problems
In applications where categorical labels follow a natural hierarchy, classification methods that exploit the label structure often outperform those that do not.
Vertex Nomination, Consistent Estimation, and Adversarial Modification
Given a pair of graphs $G_1$ and $G_2$ and a vertex set of interest in $G_1$, the vertex nomination (VN) problem seeks to find the corresponding vertices of interest in $G_2$ (if they exist) and produce a rank list of the vertices in $G_2$, with the corresponding vertices of interest in $G_2$ concentrating, ideally, at the top of the rank list.
