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Found 10 papers, 6 papers with code
MLFMF: Data Sets for Machine Learning for Mathematical Formalization
The collection includes the largest Lean~4 library Mathlib, and some of the largest Agda libraries: the standard library, the library of univalent mathematics Agda-unimath, and the TypeTopology library.
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.
Unsupervised Feature Ranking via Attribute Networks
The need for learning from unlabeled data is increasing in contemporary machine learning.
Discovering outliers in the Mars Express thermal power consumption patterns
The Mars Express (MEX) spacecraft has been orbiting Mars since 2004.
GalaxAI: Machine learning toolbox for interpretable analysis of spacecraft telemetry data
We present GalaxAI - a versatile machine learning toolbox for efficient and interpretable end-to-end analysis of spacecraft telemetry data.
ReliefE: Feature Ranking in High-dimensional Spaces via Manifold Embeddings
The utility of ReliefE for high-dimensional data sets is ensured by its implementation that utilizes sparse matrix algebraic operations.
Multi-Label Classification
Vocal Bursts Intensity Prediction
Ensemble- and Distance-Based Feature Ranking for Unsupervised Learning
In this work, we propose two novel (groups of) methods for unsupervised feature ranking and selection.
Feature Ranking for Semi-supervised Learning
This poses a variety of challenges for the existing machine learning methods: coping with dataset with a large number of examples that are described in a high-dimensional space and not all examples have labels provided.
Fuzzy Jaccard Index: A robust comparison of ordered lists
In real-life, and in particular high-dimensional domains, where only a small percentage of the whole feature space might be relevant, a robust and confident feature ranking leads to interpretable findings as well as efficient computation and good predictive performance.
Machine learning for predicting thermal power consumption of the Mars Express Spacecraft
The thermal subsystem of the Mars Express (MEX) spacecraft keeps the on-board equipment within its pre-defined operating temperatures range.
