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Found 9 papers, 2 papers with code
Efficient Generator of Mathematical Expressions for Symbolic Regression
We empirically show that HVAE can be trained efficiently with small corpora of mathematical expressions and can accurately encode expressions into a smooth low-dimensional latent space.
P(Expression|Grammar): Probability of deriving an algebraic expression with a probabilistic context-free grammar
We then present specific grammars for generating linear, polynomial, and rational expressions, where algorithms for calculating the probability of a given expression exist.
Boosting the Performance of Quantum Annealers using Machine Learning
Noisy intermediate-scale quantum (NISQ) devices are spearheading the second quantum revolution.
Explaining the Performance of Multi-label Classification Methods with Data Set Properties
Here, we analyze 40 MLC data sets by using 50 meta features describing different properties of the data.
Comprehensive Comparative Study of Multi-Label Classification Methods
Several studies provide reviews of methods and datasets for MLC and a few provide empirical comparisons of MLC methods.
Probabilistic Grammars for Equation Discovery
Equation discovery, also known as symbolic regression, is a type of automated modeling that discovers scientific laws, expressed in the form of equations, from observed data and expert knowledge.
Equation Discovery for Nonlinear System Identification
In this paper, recent developments of the equation discovery method called process-based modeling, suited for nonlinear system identification, are elaborated and illustrated on two continuous-time case studies.
Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems
This task involves numerous evaluations of a computationally expensive objective function.
The Influence of Feature Representation of Text on the Performance of Document Classification
In this study, we measure the performance of the document classifiers trained using the method of random forests for features generated the three models and their variants.
