AIMC Topic: Probability

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Generative Adversarial Networks are special cases of Artificial Curiosity (1990) and also closely related to Predictability Minimization (1991).

Neural networks : the official journal of the International Neural Network Society
I review unsupervised or self-supervised neural networks playing minimax games in game-theoretic settings: (i) Artificial Curiosity (AC, 1990) is based on two such networks. One network learns to generate a probability distribution over outputs, the ...

Noise can speed backpropagation learning and deep bidirectional pretraining.

Neural networks : the official journal of the International Neural Network Society
We show that the backpropagation algorithm is a special case of the generalized Expectation-Maximization (EM) algorithm for iterative maximum likelihood estimation. We then apply the recent result that carefully chosen noise can speed the average con...

Extracting boolean and probabilistic rules from trained neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper presents two approaches to extracting rules from a trained neural network consisting of linear threshold functions. The first one leads to an algorithm that extracts rules in the form of Boolean functions. Compared with an existing one, th...

Common Audiological Functional Parameters (CAFPAs) for single patient cases: deriving statistical models from an expert-labelled data set.

International journal of audiology
Statistical knowledge about many patients could be exploited using machine learning to provide supporting information to otolaryngologists and other hearing health care professionals, but needs to be made accessible. The Common Audiological Function...

iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification.

Scientific reports
With the advent of personalized medicine, there is a movement to develop "smaller" and "smarter" microdevices that are able to distinguish similar cancer subtypes. Tumor cells display major differences when compared to their natural counterparts, due...

Patient selection for proton therapy: a radiobiological fuzzy Markov model incorporating robust plan analysis.

Physical and engineering sciences in medicine
While proton therapy can offer increased sparing of healthy tissue compared with X-ray therapy, it can be difficult to predict whether a benefit can be expected for an individual patient. Predictive modelling may aid in this respect. However, the pre...

A Multi-Modal Person Perception Framework for Socially Interactive Mobile Service Robots.

Sensors (Basel, Switzerland)
In order to meet the increasing demands of mobile service robot applications, a dedicated perception module is an essential requirement for the interaction with users in real-world scenarios. In particular, multi sensor fusion and human re-identifica...

Determining of the optimized dimensions of the Marinelli beaker containing source with inhomogeneous emission rate by using genetic algorithm coupled with MCNP and determining distribution type by neural networks.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
In order to determine the activity of C137s in soil resulting from nuclear accidents or fallouts, the best choice is to use HPGe detectors due to their best energy resolutions. In this regard, in order to enhance the detection efficiency, the Marinel...

Machine learning workflows to estimate class probabilities for precision cancer diagnostics on DNA methylation microarray data.

Nature protocols
DNA methylation data-based precision cancer diagnostics is emerging as the state of the art for molecular tumor classification. Standards for choosing statistical methods with regard to well-calibrated probability estimates for these typically highly...

Polygenic risk scores outperform machine learning methods in predicting coronary artery disease status.

Genetic epidemiology
Coronary artery disease (CAD) is the leading global cause of mortality and has substantial heritability with a polygenic architecture. Recent approaches of risk prediction were based on polygenic risk scores (PRS) not taking possible nonlinear effect...